Introduction
ESRD has a high and increasing worldwide prevalence. To reduce the global burden of ESRD, effective strategies for the detection and prevention of CKD are needed. By the end of 2012, the estimated CKD population will be more than 20 million in the United States (1) and 800 million in southern Asia (2). The detection and treatment of CKD are, thus, an important issue in health care.
To identify patients with CKD, previous studies have recommended screening for several risk factors (3–11). Age and comorbid conditions have been well documented as risk factors for CKD (12). In elderly patients, aging processes might partially contribute to CKD development: The prevalence of CKD is almost three to four times higher in these people than in the general population (13). The manner in which age interacts with other risk factors for CKD has yet to be fully elucidated. In addition, previous research on known risk factors for CKD, such as hypertension, diabetes mellitus, cardiovascular disease, and several metabolic abnormalities, in patients of different ages is limited. This lack of evidence might explain why current CKD guidelines contain no recommendations for CKD screening in different age groups (14).
The use of herbal therapies is common in Taiwan, a CKD epidemic area, and is reportedly associated with ESRD (15). Chinese herbs containing aristolochic acid can induce renal injury (16). Two case series identified an association between interstitial nephritis and the use of Chinese herbal drugs (17,18). However, these studies were predominantly hospital-based or used a case-control design rather than being based on a community survey.
We used a community-based survey to evaluate the risk factors for CKD in elderly and nonelderly patients. We hypothesized that the risk factors for CKD differ in patients of different ages and that the use of herbal therapy is one risk factor for CKD.
Materials and Methods
Study Design
Residents of Kaohsiung County, Taiwan, older than age 15 years (n=1,026,288) were considered for the survey population in 2007. A multistage stratified sampling method was then used to select 3000 participants from the Household Register Database. In the first stage, one city with a population that accounted for 27.3% of the county population and 8 of the 27 villages were randomly selected. In the second stage, probability proportional to size sampling was applied. Villages with populations <30,000 and those between 30,000 and 50,000 were weighted by 3 and 2, respectively. In the third stage, 50 districts (Li; smallest unit of administration) from the city and villages were randomly selected using probability from the second stage. In the final stage, 60 participants were randomly selected from the districts selected in the third stage. In the pilot study, the response rate was estimated as approximately one sixth; therefore, 18,000 participants were randomly selected and invited for CKD screening using the described process. This study was approved by the Institutional Review Board of Kaohsiung Medical University (KMUH-IRB-950193).
Measurements
Eighty screenings were performed in each administration unit during weekends. The selected participants were informed by mail, and they were given instructions to fast overnight for at least 10 hours. On the scheduled day, participants signed the informed consent forms and were then guided on procedures for completing the questionnaire, physical examination, blood draw, and fresh urine collection. BP was measured twice, the second time after a 15-minute rest. A third measurement was performed if the difference between the prior two measurements was >5 mmHg. The serum and urine specimens were transported to the central laboratory for further analyses.
Laboratory Tests
The blood and urine specimens were analyzed using an autoanalyzer (Roche Cobas Integra), whereas hepatitis B virus surface antigen and serum anti–hepatitis C virus antibody were analyzed using an Abbott Architect I2000 analyzer. Laboratory quality control was done regularly to verify inter- and intra-assay reproducibility. Serum creatinine was measured using the Jaffe reaction (kinetic alkaline picrate method). The serum creatinine measurement in the laboratory was traceable to an isotope dilution mass spectrometry reference. Urine albumin was measured by immunoturbidimetry and urine creatinine by the kinetic Jaffe method. Microalbuminuria was defined as an albumin-to-creatinine ratio of 30 mg/g or higher.
Definitions of CKD, Metabolic Syndrome, and Hyperuricemia
The estimated GFR (eGFR) was calculated using a four-variable Modification of Diet in Renal Disease equation (19). CKD was diagnosed according the Kidney Disease Outcomes Quality Initiative guidelines, with minor modifications (stage 3 was subcategorized as 3a [eGFR, 45–59 ml/min per 1.73 m2] or 3b [eGFR, 30–44 ml/min per 1.73 m2]) (14), and was defined as an eGFR < 60 ml/min per 1.73 m2 or proteinuria in at least the microalbuminuric stage by one measurement only. Metabolic syndrome was defined as the presence of three or more of the following five components of the modified criteria of the National Cholesterol Education Program-Adult Treatment Panel III for Asians (20): (1) waist circumference > 90 cm in men and > 80 cm in women, (2) triglyceride level ≥ 150 mg/dl, (3) HDL cholesterol level < 40 mg/dl in men and < 50 mg/dl in women, (4) fasting whole blood glucose level > 110 mg/dl or a previous diagnosis of diabetes mellitus, and (5) systolic BP ≥ 130 mmHg, diastolic BP ≥ 85 mmHg, or a previous diagnosis of hypertension. Hyperuricemia was defined as a uric acid level ≥ 7 mg/dl in men and ≥ 6 mg/dl in women.
Statistical Analyses
The sample weight was calculated according to the sampling probability of each Li by multiplying by the sampling probability of each participant. Data were stratified into two groups (using age 60 years as a cutoff value), and the analyses were performed separately in each group. Characteristics are presented as mean ± SD or percentage. An adjusted Wald test and Pearson chi-squared test were used to compare the differences in continuous or categorical variables between participants with and without CKD. Survey logistic regression was used to calculate the odds ratios and 95% confidence intervals (CIs) for CKD in univariate and multivariate analyses. In multivariate analysis, all the variables in Table 1 were force-entered to produce the final model in the overall group and in both age groups. The interaction terms between age category and associated factors were also tested. Sensitivity testing was conducted by re-performing all the analyses with age 65 years used as a cutoff value. A two-sided P value < 0.05 was considered to represent a statistically significant difference. All statistical operations were performed using Stata software, version 12.0 (Stata Corp., College Station, TX). GraphPad Prism 5.0 was used for plotting (GraphPad Software Inc., San Diego, CA).
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Table 1: Characteristics of study cohort by age
Results
Representative Sample
The community-based survey included 3352 participants, with a response rate of approximately 18.6%. The mean age of the cohort was 47.5 years and the mean age of the sampling pool was 41.4 years.
Characteristics of CKD Patients
The prevalence of CKD was 20.5% overall 19.4% (95% CI, 18.0%–20.7%) after weighted adjustment for sampling, and 15.1% (95% CI, 15.0%–15.2%) after further standardization for age and sex. Table 1 displays the participants’ demographic characteristics and biochemical test results. Similar to findings from previous studies, the CKD patients were older, with fewer years of education and lower income than the participants without CKD. The CKD patient population also had a higher prevalence of hypertension, diabetes mellitus, CKD, cardiovascular disease, stroke, gout, and urinary tract diseases than the non-CKD participants. Patient awareness of CKD was very low, approximately 5.6%. In addition to expected laboratory abnormalities, patients with CKD had a higher percentage of HCV infection than participants without CKD (Table 1).
Prevalence of CKD according to Age and Metabolic Syndrome
As shown in Figure 1, the prevalence of CKD was four times higher in participants age ≥60 years and older than in those <60 years (45.5% versus 11.6% after weighted adjustment). In almost all age groups, the prevalence of CKD was higher in women than in men. Figure 2 shows the prevalence and proportion of CKD stages in both age groups. The prevalence of CKD in the nonelderly decreased as CKD stage increased (stages 1 and 2, 7.2%; stage 3, 4.1%; and stages 4 and 5, 0.3%). Three quarters of the nonelderly CKD patients had stage 1 and 2 CKD, with proteinuria the main clinical presentation (Figure 2B). Approximately half of the elderly patients with CKD had stage 3a CKD, and less than one third had stage 1 and 2 CKD (Figure 2B).
Figure 1: Prevalence of CKD by sex in Kaohsiung County residents older than 15 years.
Figure 2: Prevalence and proportion of CKD stages in non-elderly and elderly groups. (A) Prevalence by CKD stages in age <60 years and age ≥60 years. (B) Proportion of CKD stages by age <60 years and ≥60 years.
Metabolic syndrome is common in elderly and nonelderly patients with CKD (Table 2). In this study, all components of metabolic syndrome were associated with CKD in both age groups except lower HDL cholesterol, which was associated with CKD in the nonelderly patients only.
Table 2: Univariate analyses of the association between CKD and metabolic syndrome by age
Other Risk Factors for CKD in Elderly and Nonelderly Patients
Irrespective of having CKD, nearly 20% and 40% of all participants consumed Chinese herbs and health supplements, respectively (Table 1). However, univariate analysis in both age groups failed to identify any specific Chinese herbal formula that was associated with CKD (data not shown). Surprisingly, only 15.5% of the nonelderly patients and 6.1% of the elderly patients could name the Chinese herb they were taking.
Table 3 shows the independent factors for CKD in elderly and nonelderly participants as well as the interactions with age. In elderly patients, medical history of diabetes mellitus, CKD, stroke, oral use of analgesics, and not using analgesic injections were positively associated with CKD. In nonelderly patients, gout, hepatitis B virus infection, and the use of the Chinese herbal medicine Long Dan Xie Gan Tang were positively associated with CKD. The oral use of analgesics, however, was negatively associated with CKD. Age, annual income, metabolic syndrome, hyperuricemia, and hemoglobin were significantly associated with CKD in both age groups. Among these independently significant factors, annual income, oral use of analgesics, and hyperuricemia showed a significant interaction with age. The results were similar if older age was defined as ≥65 years except that some of the comorbid conditions shifted their significant association from the elderly to the nonelderly.
Table 3: Multivariate analyses of associations between significant factors and CKD by age
Discussion
Using a multistage community-based survey, we identified a weighted prevalence of CKD of 19.4% (corresponding to nearly 1 in 5 persons) in an area with a high prevalence of dialysis dependency. Results indicated that patients with CKD of different age groups have differing clinical presentations and associated factors. In elderly patients, medical history of diabetes mellitus, CKD, stroke, the use of analgesics, and using analgesic injection were associated with CKD. In nonelderly participants, the use of analgesics was associated with lower rather than higher odds of CKD. Overall, herbal therapy was not associated with CKD; however, the use of Long Dan Xie Gan Tang was independently associated with CKD in nonelderly participants.
Previous studies on CKD identified prevalence rates ranging from 10.8% to 19.1% worldwide (8,10). In addition to the varying characteristics of areas, variations in screening tools and sampling methods might have caused the differences in the identified prevalence rates (21). Some studies used urine dipstick tests to evaluate proteinuria. This method can fail to identify microalbuminuria in stage 1 and 2 CKD. In studies that used urine dipsticks for screening, the prevalence of stage 1 and 2 CKD was 2.3% in Japan and 3.8% in Taiwan. In studies that used the urinary albumin-to-creatinine ratio as an evaluation method, the prevalence of stages 1 and 2 CKD was 9.1% in China, 5.0% in the United States, and 8.6% in the present cohort (3,6,7,10). The sampling methods in community-based screening studies are always used to negotiate between convenience and the generalization of the results. Bias can occur with inclusion of older patients, a higher-risk subgroup, or participants with higher socioeconomic status (7,22,23). The common trend among all previous studies was increasing CKD prevalence with increasing mean age. Our use of multistage sampling, conducting of screening in participants’ residential areas, and use of urinary albumin-to-creatinine ratio for the evaluation of proteinuria might have increased the reliability of the results.
In this study, the prevalence of CKD was four times higher in elderly patients than in nonelderly participants. As was seen in other previous studies, the patients with stage 3a CKD predominantly contributed to the higher prevalence of CKD in the elderly patients compared with the nonelderly patients (24). It is not yet known whether an eGFR only slightly below 60 ml/min per 1.73 m2 would increase elderly patients’ future risk for ESRD and death. In this study’s elderly patients, the association between metabolic syndrome and CKD was attenuated at stage 3a and became even smaller when eGFR was >55 ml/min/1.73 m2. Medical history of diabetes mellitus and stroke were positively associated with CKD in elderly patients but not in the nonelderly group. Considering the chronicity of these diseases and their late-middle-age onset, the occurrence of renal consequences within a few years of disease development is an expected outcome. It might, therefore, be useful if the recommendations for CKD screening considered the potential interaction between age and comorbid conditions. Further studies are needed to determine whether implementing CKD screening according to age and comorbidity can improve clinical outcomes.
In this study, nonelderly patients with CKD typically presented with proteinuria, whereas elderly patients typically presented with low eGFR. Urine analysis was enough to identify a high proportion of our nonelderly patients with CKD; therefore, the efficiency of a routine CKD screening test, including both blood and urine sampling, in nonelderly adults might be doubtful. Using that type of CKD screening method in young adults, for example, might reduce accessibility and, thus, the screening rate. This study is also the first to show that hepatitis B virus infection is associated with CKD in nonelderly patients in a hepatitis endemic area (25). It is well known that hepatitis B virus infection increases the risk for nephropathy (26); however, no previous study has identified its association with CKD. It is possible that the use of urinary albumin-to-creatinine ratio as a screening tool, and the stratification of patients according to age, might have increased the significance of this study’s results. In our group’s previous large-scale surveys, patients with hepatitis C, but not those with hepatitis B, had a higher risk for CKD (27,28). According to international consensus, changes in albuminuria can be used for contemporary CKD staging and prediction of clinical outcome (29). However, using albuminuria screening for routine survey has several disadvantages. First, it is costly, and therefore cannot be applied in a large-scale setting. Second, at least two positive results are needed for diagnosis. This can make the diagnostic process time-consuming and complicate data interpretation. Third, no evidence suggests that early diagnosis of CKD leads to improved outcome. Further investigation is therefore needed to evaluate the usefulness of quantitative albuminuria assessment for the identification of CKD and its risk factors, and for improving clinical outcome.
The use of nonprescribed medications, traditional herbs, or health supplements is relatively common in patients with CKD. In CKD education, it remains controversial as to whether information should be provided on substances with renal side effects that have yet to be clarified. Although investigators have widely investigated aristolochic acid and its nephrotoxic effects, most of these investigations were case-control studies (30). To our knowledge, this community-based study is the first to identify that the use of Chinese herbs containing aristolochic acid might increase the risk for CKD. Results indicated that Long Dan Xie Gan Tang was associated with CKD prevalence in nonelderly participants. This combined Chinese herb formula, which includes Mu Tong, possibly contains aristolochic acid. Use of Chinese herbs containing aristolochic acid was not uncommon before it was banned in 2003; this substance accounted for 3% of all qualified prescriptions at Taiwan (31). Given that a large proportion of consumers tend to be unfamiliar with the ingredients of the Chinese herbs they were taking and very few are prescribed to take the formula Long Dan Xie Gan Tang, this result is needed to be reconfirmed in the future. Although investigators have extensively evaluated the renal side effects of analgesics, little is known concerning the renal effects of Chinese herbal medications. The use of analgesics is generally prohibited in patients with CKD. This has led to the undertreatment of pain in CKD and is consistent with this study’s finding that patients with CKD use fewer analgesics than the general population. Because the renal adverse effects of most herbs are uncertain, further evidence is needed to facilitate the education of patients with CKD on the avoidance of potentially nephrotoxic agents.
This study has several strengths. First, its complex sampling approach was used in an area with high ESRD prevalence. Conducting screening near the patients’ residences increased the response rate. Second, stratifying the cohort according to age enabled the identification of several age-specific risk factors for CKD. Third, the laboratory data were collected in one laboratory; this avoided bias during the measurement of serum creatinine. Using the urinary albumin-to-creatinine ratio as the index of proteinuria further enabled the identification of novel factors for CKD.
This study also has a few limitations. First, its cross-sectional design and the diagnosis of CKD are based on one interview. Second, selection bias is possible: The response rate for multistage sampling was approximately 20%. Third, selected patient information was collected using a questionnaire, a method that can suffer from recall bias. It was also difficult to quantify herbal medicine dosages using this method of data collection. Finally, using the four-variable Modification of Diet in Renal Disease equation to calculate eGFR might be inappropriate in Asian patients.
In conclusion, this study identified a high prevalence of CKD in an area with a high prevalence of dialysis dependency. Results indicated that CKD patients of different ages have differing clinical presentations and associated risk factors. These findings might facilitate the improvement of current screening strategies for CKD and increase awareness of CKD. The higher prevalence of CKD in the elderly with comorbid conditions suggests that regular measurement of renal function is mandatory in these populations, while the use of Chinese herbs might be an issue related to CKD in the nonelderly. Physicians responsible for higher-risk patients should consider the interaction of age with specific factors for CKD and arrange appropriate screening accordingly.
Disclosures
None.
Acknowledgments
The authors would like to express their appreciation to staff members in local units of the Branch of Health, Kaohsiung County, the CKD study team at Kaohsiung Medical University Hospital, and students of the Department of Public Health, Kaohsiung Medical University for their contributions to administrative works, data collection, laboratory testing, and data processing.
This study was supported by a grant from the Bureau of Health Promotion, Department of Health, Executive Yuan, Taiwan, Republic of China (DOH-96-HP-1102).
Published online ahead of print. Publication date available at www.cjasn.org.
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