American Journal of Kidney Diseases
Volume 55, Issue 5 , Pages 856-866, May 2010

Prevalence and Risk Factors for CKD in Spouses and Relatives of Hemodialysis Patients

  • Jer-Chia Tsai, MD

      Affiliations

    • Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
    • Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
    • ,
  • Szu-Chia Chen, MD

      Affiliations

    • Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
    • Department of Internal Medicine, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
    • ,
  • Shang-Jyh Hwang, MD

      Affiliations

    • Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
    • Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
    • ,
  • Jer-Ming Chang, MD, PhD

      Affiliations

    • Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
    • Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
    • Department of Internal Medicine, Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
    • ,
  • Ming-Yen Lin, MPH

      Affiliations

    • Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
    • ,
  • Hung-Chun Chen, MD, PhD

      Affiliations

    • Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan
    • Faculty of Renal Care, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
    • Corresponding Author InformationAddress correspondence to Hung-Chun Chen, MD, PhD, Division of Nephrology, Department of Internal Medicine, Chung-Ho Memorial Hospital, Kaohsiung Medical University, 100 Shih-Chuan 1st Rd, Kaohsiung 807, Taiwan

Received 18 May 2009; accepted 11 December 2009. published online 16 February 2010.

Article Outline

Background

A higher prevalence of chronic kidney disease (CKD) has been found in genetic relatives of patients with end-stage renal disease. However, the risk of CKD in nongenetic spouses of patients with end-stage renal disease is still unknown.

Study Design

Cross-sectional study.

Setting & Participants

196 first- and second-degree relatives and 95 spouses of 178 hemodialysis (HD) patients were enrolled. Two sex- and age-stratified matched counterpart controls were randomly selected from the population of a community screening program for CKD.

Predictors

Relatives or spouses of HD patients and kidney disease risk factors.

Outcomes

Prevalence of CKD (albuminuria or low estimated glomerular filtration rate).

Measurement

Albuminuria (urine albumin-creatinine ratio ≥ 30 mg/g), low estimated glomerular filtration rate (<60 mL/min/1.73 m2), and kidney disease risk factors of age, hypertension, diabetes mellitus, metabolic syndrome, and lifestyle.

Results

A significantly higher prevalence of CKD was found in relatives (15.8% vs 7.5%; P = 0.01) and spouses (41.1% vs 15.8%; P < 0.001) of HD patients compared with their counterpart controls. Multiple logistic regression analysis showed that age (OR, 1.05) and hypertension (OR, 3.13) were significant independent risk factors for CKD in relatives of HD patients, whereas diabetes mellitus (OR, 3.51) was a significant risk factor for CKD in spouses of HD patients. For all pooled participants, being relatives (OR, 2.55) or spouses (OR, 2.80) of HD patients, age (OR, 1.06), female sex (OR, 1.81), diabetes mellitus (OR, 3.95), hypertension (OR, 1.85), and hyperuricemia (OR, 2.06) were independent significant risk factors for CKD.

Limitations

Cross-sectional research design, single laboratory measurement, and limited numbers of participants.

Conclusions

A comprehensive screening program for CKD is equally important in both relatives and spouses of HD patients, especially for participants with the renal risk factors of older age, hypertension, and diabetes mellitus. Spousal concordance of CKD suggests that the shared environmental factors and health behaviors might have important roles in the development of CKD.

Index Words: Chronic kidney disease (CKD), albuminuria, relatives, spouses, hemodialysis (HD), renal risk factors

 

Chronic kidney disease (CKD) has been recognized as a global public health problem with increasing incidence and prevalence and high morbidity and mortality.1, 2 The major risk factors for CKD include older age, family history of CKD, diabetes mellitus, hypertension, cardiovascular disease, metabolic syndrome, and obesity.3 Targeted screening for these high-risk populations has been proposed as a comprehensive public health strategy to ensure the cost-effectiveness of CKD prevention and management and achieve improved patient outcomes.4, 5

Family members of patients with end-stage renal disease (ESRD) have been found to have a higher risk of CKD.6, 7, 8, 9, 10, 11, 12, 13 However, high variability in the prevalence of CKD in relatives of patients with CKD may be caused by differences in ethnicities and screening methods.11, 13, 14, 15 Additionally, the prevalence of associated renal risk factors needs to be identified.

Taiwan has the highest incidence and second highest prevalence of ESRD in the world.16, 17 This epidemic of CKD has lead to an increased risk of all-cause mortality.18 Large-scale epidemiologic surveys in Taiwan have identified several important risk factors for CKD, including lack of awareness, old age, diabetes mellitus, hypertension, hyperlipidemia, female sex, low socioeconomic status, and use of herbal medicine.19, 20, 21 However, it still is uncertain whether a family history of CKD has a role in the development of CKD in Taiwan.

Moreover, familial clustering of CKD and ESRD may be explained by the dual effects of genetic susceptibility and environmental exposures.10, 11, 22 Spouses of patients with ESRD were considered to be nongenetic controls for studying the family clustering of CKD.12 However, we propose that spouses of patients with ESRD also could act as candidates for studying the role of environmental factors in developing CKD. Thus, this study aims to investigate the prevalence of CKD and its associated risk factors in both genetic relatives and nongenetic spouses of patients with ESRD.

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Methods 

Study Participants and Design 

We enrolled 196 first- and second-degree relatives of hemodialysis (HD) patients (HD-relatives group) and 95 spouses of HD patients (HD-spouses group) from 178 index HD patients from the Kaohsiung City area, Taiwan (men/women, 71/107; mean age, 58.1 ± 12.6 [standard deviation (SD)] years) with dialysis duration of 3 months to 21 years. Underlying causes for HD included chronic glomerular diseases (n = 91; 51.1%), diabetic nephropathy (n = 59; 33.2%), tubulointerstitial diseases (n = 13; 7.3%), hypertension (n = 10; 5.6%), and other renal diseases (n = 5; 2.8%). HD patients with inherited kidney disease, such as autosomal dominant polycystic kidney disease, were excluded for study.

We attempt to contact all first- and second degree relatives of HD patients. In our original registration database, 479 relatives' (209 first degree and 270 second degree) records were well documented. About 59%, 283 (489 minus 196) of 479, of relatives of HD patients were not enrolled because of refusal, geographic reasons, loss of contact, or lack of information. For the other 83 HD patients for whom spouses who were not enrolled, the main reasons were that spouses declined to participate or HD patients were unmarried, widowed, divorced, or separated.

Controls were selected from the population participating in a community screening program that consisted of 2,762 participants in Kaohsiung City area in 2005 (men/women, 771/1,991; mean age, 52.5 ± 13.2 years). Sample sizes of each age-stratified group of ≤40, 41-65, and >65 years were 766, 1,524, and 472 participants, respectively. In selecting controls for HD relatives, 387 sex- and age-stratified matched persons were randomly selected as controls. In selecting for HD spouses, 190 sex- and age-stratified matched persons were randomly selected as controls. The study was approved by the institutional review board and conducted according to the principles expressed in the Declaration of Helsinki. Informed consent was obtained from all study participants and controls.

Laboratory Investigations 

Biochemical data were measured from fasting blood samples using an autoanalyzer (COBAS Integra 400 plus; Roche Diagnostics, www.roche.com/diagnostics/). Urinary albumin and creatinine were measured from 1 spot urine sample using the same analyzer. Intra-assay coefficients of variation for urinary albumin and creatinine were 1.09% and 0.74%, respectively. Interassay coefficients of variation for urinary albumin and creatinine were 1.48% and 0.94%, respectively. Proteinuria and hematuria were examined using dipstick tests (Hema-Combistix; Bayer Diagnostics, www.bayer.com), for which a test result ≥ 1+ was defined as a positive result.

Definitions 

Albuminuria, CKD, and CKD Awareness 

Estimated glomerular filtration rate (eGFR) was measured using the 4-variable equation in the Modification of Diet in Renal Disease (MDRD) Study.23 Albuminuria was defined as urinary albumin-creatinine ratio ≥ 30 mg/g with eGFR ≥ 60 mL/min/1.73 m2, and low eGFR was defined as < 60 mL/min/1.73 m2 based on the National Kidney Foundation's Kidney Disease Outcomes Quality Initiative guidelines.24 CKD was defined as the presence of albuminuria or low eGFR. CKD awareness was defined as participant self-report that they had been told by a physician that they had kidney disease or impaired renal function.19

Diabetes Mellitus and Hypertension 

Diabetes mellitus was defined as fasting blood glucose level > 126 mg/dL, diabetes mellitus diagnosed previously by a physician, or use of hypoglycemic agents. Blood pressure (BP) was measured using a mercury sphygmomanometer in a seated position at rest for at least 5 minutes. Hypertension was defined as systolic BP ≥ 140 mm Hg or diastolic BP ≥ 90 mm Hg, hypertension previously diagnosed by a physician, or use of antihypertensive medications.

Metabolic Syndrome, Hypertriglyceridemia, Hypercholesterolemia, Hyperuricemia, and Obesity 

Metabolic syndrome was defined as having 3 of the following 5 abnormalities based on the standard of the National Cholesterol Education Program Adult Treatment Panel III25 and modified criteria for Asians26: (1) abdominal obesity, defined as waist circumference > 90 cm for men and > 80 cm for women; (2) hypertriglyceridemia, defined as triglyceride concentration ≥ 150 mg/dL; (3) low high-density lipoprotein cholesterol concentration, defined as high-density lipoprotein cholesterol concentration < 40 mg/dL in men and < 50 mg/dL in women; (4) hyperglycemia, defined as fasting whole-blood glucose concentration ≥ 110 mg/dL or diabetes mellitus; and (5) high BP, defined as systolic BP ≥ 130 mm Hg, diastolic BP ≥ 85 mm Hg, or physician-diagnosed or -treated hypertension. In addition, hypercholesterolemia and hyperuricemia were defined as serum cholesterol level ≥ 240 mg/dL and uric acid ≥ 7 mg/dL, respectively. Body mass index was calculated as the ratio of weight in kilograms divided by the square of height in meters. Obesity was defined as body mass index > 27 kg/m2 according to criteria modified for Asians.26

Questionnaire 

All study participants completed a questionnaire survey to provide information about sociodemographic data, personal and family history of kidney diseases, diabetes mellitus, hypertension, use of herbal medicine and analgesics, and lifestyle regarding smoking and consumption of alcohol or betel nut. For spouses of HD patients, more information was asked about status of marriage and cohabitation, and dietary habits.

Statistical Analysis 

Data are expressed as mean ± SD. Differences in variables between the 2 groups or spousal concordance were analyzed using χ2 test for categorical variables or independent t test for continuous variables. Multiple logistic regression analysis was used to identify the independent significance of associated risk factors for CKD. A mixed-effect model was used to adjust family-clustering effect. A significant difference was considered for P < 0.05. Statistical analysis was performed using SPSS 12.0 statistical software for Windows (SPSS Inc, www.spss.com).

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Results 

Clinical Characteristics, Prevalence of CKD, and Associated Risk Factors 

Relatives of HD Patients 

Clinical characteristics of HD relatives and matched controls are listed in Table 1. Although the mean age of HD relatives was significantly younger than that of controls (38.4 ± 13.8 vs 41.4 ±13.2 years; P = 0.01), the prevalence of albuminuria was significantly higher in HD relatives compared with controls (10.7% vs 4.1%; P = 0.01). There was no difference in the prevalence of low GFR between these 2 groups. The prevalence of CKD was significantly higher in HD relatives compared with controls (15.8% vs 7.5%; P = 0.01). There was no significant difference in related variables except for age (37.5 ± 13.7 vs 44.1 ± 13.9 years; P < 0.05) between first- and second-degree HD relatives.

Table 1. Comparison of Characteristics and Renal Outcomes Between Relatives of HD Patients and Controls
CharacteristicsRelatives of HD Patients (n = 196)Controls (n = 387)P
Risk factors
Age (y)38.4±13.841.4±13.20.01
Men90(45.9)185(47.8)0.7
Diabetes mellitus9(4.6)7(1.8)0.05
Hypertension53(27.0)74(19.1)0.03
Metabolic syndrome39(19.9)49(12.7)0.02
Body mass index > 27 kg/m254(27.6)52(13.4)<0.001
Use of herbal medicine11(5.6)17(4.4)0.5
Use of analgesics5(2.6)9(2.3)0.8
Smoking (ever vs never)42(21.4)46(11.9)<0.001
Alcohol (ever vs never)61(31.1)133(34.4)0.9
Betel nut (ever vs never)13(6.6)18(4.7)0.2
Family history of diabetes64(32.7)91(23.5)0.02
Family history of hypertension84(42.9)108(27.9)0.01
Family history of CKD196(100)23(5.9)<0.001
Awareness of kidney disease1/31(3.2)1/29(4.0)0.9
Laboratory data
Serum urea nitrogen (mg/dL)12.8±4.413.1±3.50.4
Serum creatinine (mg/dL)0.98±0.240.93±0.170.02
eGFRa (mL/min/1.73 m2)82.0±14.683.9±13.00.1
Triglycerides (mg/dL)139.7±106.7128.9±89.00.2
Cholesterol (mg/dL)199.6±36.6197.7±37.20.6
Uric acid (mg/dL)6.1±1.75.8±1.60.03
Outcomes
Proteinuria28(14.3)65(16.8)0.4
Hematuria17(8.7)37(9.6)0.7
Albuminuriab21(10.7)16(4.1)0.01
Low eGFRc10(5.1)13(3.4)0.3
CKDd31(15.8)29(7.5)0.01

Note: Data expressed as mean ± standard deviation or number (percentage). Conversion factors for units: serum urea nitrogen in mg/dL to mmol/L, ×0.357; serum creatinine in mg/dL to μmol/L, ×88.4; eGFR in mL/min/1.73 m2 to mL/s/1.73 m2, ×0.0167; triglycerides in mg/dL to mmol/L, ×0.011; cholesterol in mg/dL to mmol/L, ×0.026; uric acid in mg/dL to mmol/L, ×0.059.

Abbreviations: CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; HD, hemodialysis.

aMeasured using the 4-variable Modification of Diet in Renal Disease Study equation.

bDefined as urine albumin-creatinine ratio ≥ 30 mg/g with eGFR ≥ 60 mL/min/1.73 m2.

cDefined as eGFR < 60 mL/min/1.73 m2.

dDefined as albuminuria (urinary albumin-creatinine ratio ≥ 30 mg/g with eGFR ≥ 60 mL/min/1.73 m2) or low eGFR (<60 mL/min/1.73 m2).

Regarding the associated renal risk factors, rates of diabetes mellitus, hypertension, and metabolic syndrome were higher in HD relatives than controls (Table 1). Additionally, HD relatives had a higher body mass index, increased likelihood of smoking, and more prevalent family history of diabetes mellitus, hypertension, and CKD compared with controls (Table 1). Univariate analysis between subgroups of HD relatives with and without CKD showed that older age, diabetes mellitus, hypertension, and metabolic syndrome were associated with risk of CKD in HD relatives (Table 2). Significant factors for CKD in univariate analysis were included as variables for additional multiple logistic regression analysis. It confirmed that age (odds ratio [OR], 1.05) and hypertension (OR, 3.13) were independent significant factors for CKD in HD relatives (Table 3). To adjust the family-clustering effect for different numbers (from 1-4) of relatives within each family, we performed a mixed-effect model for the HD relatives' analysis. It showed that age (P = 0.002), diabetes mellitus (P = 0.02), and hypertension (P = 0.002) were still significant risk factors for CKD.

Table 2. Comparison of Associated Risk Factors Between Relatives of HD Patients With and Without CKD

Note: Data expressed as mean ± standard deviation or number (percentage). CKD defined as albuminuria (urinary albumin-creatinine ratio ≥ 30 mg/g with eGFR ≥ 60 mL/min/1.73 m2) or low eGFR (< 60 mL/min/1.73 m2). Conversion factors for units: eGFR in mL/min/1.73 m2 to mL/s/1.73 m2, ×0.0167; triglycerides in mg/dL to mmol/L, ×0.011; cholesterol in mg/dL to mmol/L, ×0.026; uric acid in mg/dL to mmol/L, ×0.059

Abbreviations: CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; HD, hemodialysis.

aMeasured using the 4-variable Modification of Diet in Renal Disease Study equation.

Table 3. Multiple Logistic Regression Analysis of Associated Risk Factors for CKD in Relatives of HD Patients
VariableOR (95% CI)P
Age (/y)1.05(1.02-1.09)0.01
Men0.47(0.19-1.17)0.1
Diabetes4.40(0.81-23.78)0.09
Hypertension3.13(1.16-8.40)0.02
Metabolic syndrome1.49(0.52-4.22)0.5
Cholesterol ≥ 240 mg/dL1.40(0.47-4.19)0.6

Note: Conversion factor for serum cholesterol in mg/dL to mmol/L, ×0.026.

Abbreviations: CI, confidence interval; CKD, chronic kidney disease; HD, hemodialysis; OR, odds ratio.

Spouses of HD Patients 

Clinical characteristics of HD spouses and matched controls are listed in Table 4. eGFR was significantly lower in HD spouses than controls (68.9 ± 16.8 vs 75.0 ± 13.9; P = 0.01). A significantly higher prevalence of albuminuria and low eGFR was found in HD spouses compared with controls (21.1% vs 6.3%; P < 0.001; 20.0% vs 9.5%; P = 0.01, respectively). The prevalence of CKD was significantly higher in HD spouses compared with controls (41.1% vs 15.8%; P = 0.01). Accordingly, spousal concordance of CKD was evident.

Table 4. Comparison of Characteristics and Renal Outcomes Between Spouses of HD Patients and Their Controls
CharacteristicsSpouses of HD Patients (n = 95)Controls (n = 190)P
Risk factors
Age (y)58.4±10.358.8±12.20.8
Men49(51.6)98(51.6)0.9
Diabetes mellitus17(17.9)15(7.9)0.01
Hypertension44(46.3)59(31.1)0.01
Metabolic syndrome25(26.3)37(19.5)0.2
Body mass index > 27 kg/m218(18.9)31(16.3)0.6
Use of herbal medicine15(15.8)10(5.3)0.01
Use of analgesics8(8.4)4(2.1)0.02
Smoking (ever vs never)24(25.3)26(13.7)0.01
Alcohol (ever vs never)20(21.1)57(3)0.2
Betel nut (ever vs never)4(4.2)8(4.2)0.9
Family history of diabetes16(16.8)42(22.1)0.3
Family history of hypertension30(31.6)55(28.9)0.6
Family history of CKD6(6.3)5(2.6)0.1
Awareness of kidney disease5/39(12.8)1/30(3.3)0.2
Laboratory data
Serum urea nitrogen (mg/dL)16.4±9.215.0±4.40.2
Serum creatinine (mg/dL)1.14±0.700.99±0.250.04
eGFRa (mL/min/1.73 m2)68.9±16.875.0±13.900.01
Triglycerides (mg/dL)143.6±122.2138.3±80.50.7
Cholesterol (mg/dL)210.7±49.2205.6±40.90.4
Uric acid (mg/dL)6.3±1.86.1±1.50.3
Outcomes
Proteinuria15(15.8)28(14.7)0.8
Hematuria8(8.4)16(8.4)0.9
Albuminuriab20(21.1)12(6.3)<0.001
Low eGFRc19(20.0)18(9.5)0.01
CKDd39(41.1)30(15.8)<0.001

Note: Data expressed as mean ± standard deviation or number (percentage). Conversion factors for units: serum urea nitrogen in mg/dL to mmol/L, ×0.357; serum creatinine in mg/dL to μmol/L, ×88.4; eGFR in mL/min/1.73 m2 to mL/s/1.73 m2, ×0.0167; triglycerides in mg/dL to mmol/L, ×0.011; cholesterol in mg/dL to mmol/L, ×0.026; uric acid in mg/dL to mmol/L, ×0.059.

Abbreviations: CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; HD, hemodialysis.

aMeasured using the 4-variable Modification of Diet in Renal Disease Study equation.

bDefined as a urine albumin-creatinine ratio ≥ 30 mg/g with eGFR ≥ 60 mL/min/1.73 m2.

cDefined as eGFR < 60 mL/min/1.73 m2.

dDefined as albuminuria (urinary albumin-creatinine ratio ≥ 30 mg/g with eGFR ≥ 60 mL/min/1.73 m2) or low eGFR (<60 mL/min/1.73 m2).

Regarding the associated renal risk factors, there were higher rates of diabetes mellitus, hypertension, use of herbal medicine and analgesics, and habitual smoking in HD spouses compared with controls (Table 4). There was no difference in the prevalence of CKD between male and female spouses of HD patients. Univariate analysis between subgroups of spouses with and without CKD showed that older age, diabetes mellitus, hypertension, and metabolic syndrome were associated with risk of CKD in spouses of HD patients (Table 5). Significant factors for CKD in univariate analysis were included as variables for further multiple logistic regression analysis. It confirmed that diabetes mellitus (OR, 3.51) was an independent significant factor for CKD in HD relatives (Table 6).

Table 5. Comparison of Associated Risk Factors Between Spouses of HD Patients With and Without CKD

Note: Data expressed as mean ± standard deviation or number (percentage). CKD defined as albuminuria (urinary albumin-creatinine ratio ≥ 30 mg/g with eGFR ≥ 60 mL/min/1.73 m2) or low eGFR (<60 mL/min/1.73 m2). Conversion factors for units: eGFR in mL/min/1.73 m2 to mL/s/1.73 m2, ×0.0167; triglycerides in mg/dL to mmol/L, ×0.011; cholesterol in mg/dL to mmol/L, ×0.026; uric acid in mg/dL to mmol/L, ×0.059.

Abbreviations: CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate; HD, hemodialysis.

aMeasured using the 4-variable Modification of Diet in Renal Disease Study equation.

Table 6. Multiple Logistic Regression Analysis of Associated Risk Factors for CKD in Spouses of HD Patients
VariableOR (95% CI)P
Age (/y)1.04(0.98-1.09)0.2
Men1.27(0.46-3.52)0.7
Diabetes3.51(1.00-12.26)0.05
Hypertension2.17(0.79-5.95)0.1
Metabolic syndrome1.98(0.64-6.09)0.2

Abbreviations: CI, confidence interval; CKD, chronic kidney disease; HD, hemodialysis; OR, odds ratio.

Multiple Logistic Regression Analysis of Associated Risk Factors for CKD in All Pooled Participants 

To see whether the group of relatives or spouses of HD patients and other factors were still independently associated with risk of CKD, we performed a multiple logistic regression analysis for all pooled participants, including relatives or spouses of HD patients and community controls. Results further supported that relatives (OR, 2.55) or spouses (OR, 2.80) of HD patients, age (OR, 1.06), female sex (OR, 1.81), diabetes mellitus (OR, 3.95), hypertension (OR, 1.85), and hyperuricemia (OR, 2.06) were independently associated with risk of CKD (Table 7).

Table 7. Multiple Logistic Regression Analysis of Associated Risk Factors for CKD in All Pooled 868 Participants, Including Relatives or Spouses of HD Patients and Community Controls
VariableOR (95% CI)P
Age (/y)1.06(1.04-1.08)<0.001
Women (vs men)1.81(1.05-3.13)0.03
Group (vs community controls)
Relatives of HD patients2.55(1.39-4.66)0.002
Spouses of HD patients2.80(1.56-5.03)0.001
Diabetes mellitus (vs none)3.95(1.74-9.0)0.001
Hypertension (vs none)1.85(1.12-3.05)0.02
Metabolic syndrome (vs none)1.60(0.77-3.36)0.2
Body mass index > 27 kg/m20.76(0.41-1.40)0.4
Triglycerides > 150 mg/dL0.60(0.32-1.12)0.1
Cholesterol > 240 mg/dL1.30(0.73-2.32)0.4
Uric acid > 7 mg/dL2.06(1.17-3.61)0.01
Smoking (ever vs never)1.20(0.58-2.47)0.6
Alcohol (ever vs never)0.70(0.39-1.25)0.2
Betel nut (ever vs never)2.47(0.88-6.97)0.09
Family history of diabetes1.36(0.80-2.30)0.3
Family history of hypertension0.91(0.56-1.49)0.7
Awareness of kidney disease3.20(0.81-12.59)0.1

Note: Conversion factors for units: triglycerides in mg/dL to mmol/L, ×0.011; cholesterol in mg/dL to mmol/L, ×0.026; uric acid in mg/dL to mmol/L, ×0.059.

Abbreviations: CI, confidence interval; CKD, chronic kidney disease; HD, hemodialysis; OR, odds ratio.

Concordance Rates of Risk Factors Between HD Patients and Relatives or Spouses 

To determine whether concordance of associated risk factors for CKD existed between HD patients and relatives or spouses, we compared concordance rates of diabetes mellitus, hypertension, obesity, and smoking. As listed in Table 8, there was a significant concordance relationship of obesity between HD patients and relatives (8.4%; P < 0.001). There was no significant concordance relationship of other associated risk factors for CKD between HD patients and spouses.

Table 8. Concordance Rates of CKD, Diabetes Mellitus, Hypertension, Obesity, and Smoking Between HD Patients and Their Relatives or Spouses
Concordance rate (%)RelativesPSpousesP
Diabetes mellitusa2.00.311.50.07
Hypertensionb9.50.236.80.1
Obesityc8.4<0.0011.60.9
Smokingd9.30.30.0—

Note: Statistical analysis using χ2 or Fisher exact test.

Abbreviations: CKD, chronic kidney disease; HD, hemodialysis.

aThere were 190 pairs of HD patients and relatives and 95 pairs of HD patients and spouses.

bThere were 196 pairs of HD patients and relatives and 95 pairs of HD patients and spouses. Obesity defined as body mass index > 27 kg/m2.

cThere were 131 pairs of HD patients and relatives and 66 pairs of HD patients and spouses.

dThere were 54 pairs of HD patients and relatives and 88 pairs of HD patients and spouses.

Marriage, Cohabitation, and Dietary Habits Between Index HD Patients and Their Spouses 

Information for marriage, cohabitation, and dietary habits was obtained from 88 of 95 couples. Data showed that mean marriage duration was 33.5 ± 1.2 years (range, 3-55 years). The rate of cohabitation was 97.7% (86 of 88 couples). Moreover, 80.2% of these couples usually took at least 2 meals per day together.

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Discussion 

This study has shown the following major findings. There was a significantly higher prevalence of albuminuria and CKD in both HD relatives and HD spouses compared with their counterpart controls. Of renal risk factors, older age, hypertension, diabetes mellitus, and metabolic syndrome might be responsible for developing CKD in both HD relatives and HD spouses. Older age and hypertension were independent significant factors for CKD in HD relatives, whereas diabetes mellitus was an independent significant factor for CKD in HD spouses.

The finding of increased prevalences of albuminuria and CKD in HD relatives agrees with previous reports that family members of patients with CKD and ESRD were at high risk of developing CKD and ESRD.8, 9, 10, 12, 13, 27 Compared with previous screening programs for high-risk populations, the prevalence of albuminuria in HD relatives (10.7%) in this study was lower than that from the KEEP (Kidney Early Evaluation Program) program in the United States (29%),14 but similar to that from KEAPS (Kidney Evaluation and Awareness Program in Sheffield) in the United Kingdom (9.5%).13 This figure was higher than the observed rate of albuminuria in a general population-based screening program in Europe and the United States (from 5.9%-7.4%).28, 29 These discrepancies may be explained by differences in race/ethnicity and comorbid conditions of the studied population. That a higher prevalence of CKD existed despite the relatively young age (34.5 years) of our HD relatives suggests that family members of patients with ESRD should be screened as early as possible.

Furthermore, elderly and hypertensive family members of patients with ESRD were more likely to have CKD. The important role of age and hypertension in developing CKD should be reinforced. Elderly patients are the fastest growing population requiring renal replacement therapy and have a greater risk of death.16, 30 Hypertensive patients with normal renal function at baseline may develop CKD and poor cardiovascular outcomes during follow-up.31 The study by Bleyer et al32 also showed that poor glycemic and BP control were responsible for the development and progression of CKD in family members of patients with diabetic kidney disease.

More importantly, this study showed a novel finding that the prevalence of CKD (albuminuria or low eGFR) was significantly higher in HD spouses compared with controls. This result contradicts the previous report by O'Dea et al12 that spouse controls of patients with ESRD showed relatively lower prevalences compared with first-degree relatives of patients with ESRD. To our knowledge, this is the first report identifying spousal concordance of CKD. Spousal concordance of health risks and behaviors has been observed in many diseases.33 They include several major renal risk factors, such as cardiovascular disease, hypertension, metabolic syndrome, and high fasting glucose levels.34, 35, 36, 37 In this study, we also found higher rates of some diseases and health behaviors in HD spouses compared with controls, such as diabetes mellitus, hypertension, use of herbal medicine or analgesics, and smoking, as listed in Table 4. Interactions among these renal risk factors should be considered. To elucidate the pathogenic mechanism for spousal concordance of health risk and behaviors, researchers have proposed the hypotheses of assortative mating and shared environmental factors.33 In this study, cohabitation existed in nearly all couples. Thus, the shared environmental factors and health behaviors or the high prevalence of CKD in Taiwan16, 17, 19, 20 may account for the higher prevalence of CKD in HD spouses. This notion was supported by our recent report of 1 couple who developed CKD and ESRD caused by aristolochic acid nephropathy after using herbal medicine.38 Use of herbal medicine is a very common health behavior in Taiwan and has been associated with the risk of developing CKD.21 Although rates of using herbal medicine were similar in both HD spouses and controls, the possibility of nephrotoxicity caused by sharing herbal medicine or other nephrotoxic agents within couples could not be excluded.

Previous studies suggested that genetic susceptibility may account for the phenomenon of family clustering of CKD.39, 40 However, of these renal risk factors, diabetes mellitus, hypertension, and metabolic syndrome are multifactorial diseases under the influence of both genetic traits and nongenetic environmental factors.10, 22 Environmental factors, such as low socioeconomic status and lifestyle of inactivity and smoking, also should be considered as potential contributing factors for CKD.41, 42 In this study, we also identify a significant concordance of obesity between HD patients and relatives. Multiple logistic regression analysis in all pooled participants has further confirmed that relatives or spouses of HD patients, older age, female sex, diabetes mellitus, hypertension, and hyperuricemia act as independent significant risk factors for CKD. These findings suggest that both genetic traits and shared environmental factors may show multiple causal pathways to the development of CKD in relatives and spouses of HD patients. In addition, female sex is a risk factor for CKD in Taiwan20; however, the role of sex in determining renal risk is still controversial.3, 16 Moreover, hyperuricemia has been associated with the outcomes of CKD43 and warrants further study to explore its pathogenic role in developing CKD.

These findings are of significance clinically. First, they provide the rationale that a targeted screening and treatment program for CKD should be conducted not only for genetic family members of patients with ESRD, but also for their spouses, especially participants with older age, diabetes mellitus, and hypertension. This study further expands the important public health implementation of a targeted screening approach for these high-risk populations of CKD.5, 44 Second, the positive finding of spousal concordance of CKD from this study emphasizes the importance of exploring the mechanism of both genetic traits and environmental factors in the development of CKD. Third, the high detection rate of CKD using a more sensitive albuminuria method suggests that urinary albumin-creatinine ratio measurement may be a cost-effective screening approach for high-risk groups, especially for either relatives or spouses of patients with ESRD in conjunction with multiple renal risk factors. Moreover, previous studies from Europe suggest that measurement of both albuminuria and GFR is an important screening approach for CKD.15 Albuminuria with stages 1 and 2 CKD is associated with increased risk not only for the progression of CKD to ESRD, but also for cardiovascular events.15

Several limitations of our study need to be addressed. First, the diagnosis of albuminuria or CKD was based on a single laboratory measurement. However, this drawback was minimized by the accurate assays of urinary albumin and creatinine as described in the Methods section. Second, a cross-sectional study design has several inherent weaknesses, such as lack of long-term observation for outcome, difficulty interpreting the association of exposure with outcome, and susceptibility to bias resulting from low responses.45 Third, this screening study was conducted locally and with limited numbers of participants. Therefore, a comprehensive and long-term population-based screening program is needed before drawing a definitive conclusion. The ESRD Network 6 Family History Project46 and Okinawa experience47 represent the good models of targeted surveillance and early intervention on CKD for high-risk population in this aspect.

In conclusion, a comprehensive screening program for CKD is equally important in both relatives and spouses of HD patients, especially for participants with the multiple renal risk factors of older age, hypertension, and diabetes mellitus. Spousal concordance of CKD suggests that the shared environmental factors and health behaviors may have important roles in the development of CKD.

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Acknowledgements 

The authors thank their colleagues Juei-Hsin Chen, RN, Su-Chen Hwang, RN, and all staff members at the Hemodialysis Unit, Kaohsiung Medical University Hospital and Kaohsiung Municipal Hsiao-Kang Hospital, Kaohsiung Medical University, for their contribution.

Support: This study was supported by a grant from Kaohsiung Medical University Hospital and Kaohsiung Municipal Hsiao-Kang Hospital.

Financial Disclosure: None.

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 Originally published online as doi:10.1053/j.ajkd.2009.12.021 on February 16, 2010.

PII: S0272-6386(09)01659-X

doi:10.1053/j.ajkd.2009.12.021

American Journal of Kidney Diseases
Volume 55, Issue 5 , Pages 856-866, May 2010

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