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Risk factors associated with disease progression and mortality in chronic kidney disease of uncertain etiology: a cohort study in Medawachchiya, Sri Lanka

Risk factors associated with disease progression and mortality in chronic kidney disease of... Environ Health Prev Med (2012) 17:191–198 DOI 10.1007/s12199-011-0237-7 REGULAR A R T IC LE Risk factors associated with disease progression and mortality in chronic kidney disease of uncertain etiology: a cohort study in Medawachchiya, Sri Lanka • • • Lalantha Senevirathna Tilak Abeysekera Shanika Nanayakkara • • • Rohana Chandrajith Neelakanthi Ratnatunga Kouji H. Harada • • • Toshiaki Hitomi Toshiyuki Komiya Eri Muso Akio Koizumi Received: 11 July 2011 / Accepted: 8 August 2011 / Published online: 1 September 2011 The Japanese Society for Hygiene 2011 Abstract Methods This study sought to determine the possible fac- Background The alarming rise in the prevalence of tors associated with the progression and mortality of CKDu. chronic kidney disease of uncertain etiology (CKDu) The study utilized a single-center cohort registered in 2003 among the low socioeconomic farming community in the and followed up until 2009 in a regional clinic in the endemic North Central Province of Sri Lanka has been recognized region, and used a Cox proportional hazards model. as an emerging public health issue in the country. Results We repeatedly found an association between disease progression and hypertension. Men were at higher risk of CKDu than women. A significant proportion of the patients in this cohort were underweight, which empha- For the Chronic Kidney Disease of Uncertain Aetiology Consortium. sized the need for future studies on the nutritional status of A full list of Consortium members is provided in additional file 1 these patients. in the electronic supplementary material. Conclusions Compared with findings in western countries and other regions of Asia, we identified hypertension as a L. Senevirathna, T. Abeysekera, and S. Nanayakkara contributed major risk factor for progression of CKDu in this cohort. equally to this work. Electronic supplementary material The online version of this Keywords Chronic kidney disease of uncertain etiology article (doi:10.1007/s12199-011-0237-7) contains supplementary Progression  Hypertension  Sri Lanka material, which is available to authorized users. L. Senevirathna  S. Nanayakkara  K. H. Harada R. Chandrajith T. Hitomi  A. Koizumi (&) Department of Geology, Faculty of Science, Department of Health and Environmental Sciences, University of Peradeniya, Peradeniya, Sri Lanka Kyoto University Graduate School of Medicine, e-mail: rohanac@hotmail.com Kyoto, Japan e-mail: koizumi.akio.5v@kyoto-u.ac.jp N. Ratnatunga Department of Pathology, Faculty of Medicine, L. Senevirathna University of Peradeniya, Peradeniya, Sri Lanka e-mail: lalantha.s@kt3.ecs.kyoto-u.ac.jp e-mail: neela72002@yahoo.com S. Nanayakkara e-mail: shanika.n@at2.ecs.kyoto-u.ac.jp T. Komiya  E. Muso Department of Nephrology and Dialysis, Kitano Hospital, K. H. Harada Tazuke Kofukai Medical Research Institute, Osaka, Japan e-mail: harada.koji.3w@kyoto-u.ac.jp e-mail: t-komiya@kitano-hp.or.jp T. Hitomi E. Muso e-mail: hitomi.t@ax4.ecs.kyoto-u.ac.jp e-mail: muso@kitano-hp.or.jp T. Abeysekera Nephrology Unit, General Hospital (Teaching), Kandy, Sri Lanka e-mail: tilak_1@hotmail.com 123 192 Environ Health Prev Med (2012) 17:191–198 Introduction in new registrations with CKDu in the local renal clinics in the NCP. Early-morning urine samples from people Chronic kidney disease (CKD) has emerged as a global aged [5 years (except for menstruating women) were public health issue [1] and has become an important cause checked on three occasions, with an interval of 1 week of morbidity and mortality [2]. Patients with CKD consti- between consecutive samples. Subjects with proteinuria tute a significant economic burden, both directly in terms on two or more occasions were referred to renal clinics of resource utilization, and indirectly through loss of for further confirmatory investigations. Patients with productivity and impaired quality of life [3]. In the past CKDu were diagnosed after excluding known etiologies. decade, 1.1 trillion dollars have been spent on dialysis Diabetes mellitus was excluded by the absence of a worldwide [4]. Therefore, early detection of asymptomatic history, no current treatment, and hemoglobin A1C CKD patients is important because early intervention has a (HbA1C) \6.5%. Malignant hypertension was excluded reasonable chance of making a positive impact on outcome by the absence of a history of chronic and/or severe [5]. Similarly, it is important to prevent or delay disease hypertension. If blood pressure was \160/100 mmHg progression from mild to severe stages [4]. The global untreated or \140/90 mmHg with up to two antihyper- increase in the prevalence of CKD and its disproportionate tensive agents, those people were included in the CKDu burden on economically developing countries is being group. Systemic lupus erythematosus was excluded by driven by an increase in the prevalence of the main risk the absence of anti-nuclear factor and double-stranded factors for CKD; namely, diabetes, hypertension, obesity, DNA antibody. In all cases, biopsy was conducted for and aging of the population [6]. pathological diagnosis. CKDu was pathologically defined However, in the North Central Province (NCP) of Sri as a region of focal-to-diffuse interstitial fibrosis and Lanka, the dramatically increasing prevalence of CKD tubular atrophy. IgA nephropathy was excluded by during the past two decades has not been attributable to any immunostaining for IgG, IgM, IgA, and complement of these factors [7]. Thus, it has been named CKD of component C3. Urological diseases of known etiology uncertain etiology (CKDu). The majority of CKDu patients were excluded by clinical symptoms and routine in the NCP are from the low socioeconomic farming investigations. community [8]. As a result of the insidious onset and All patients who were diagnosed with CKDu were progression of the disease, these patients present in the late registered in local clinics. We recruited 143 CKDu patients stages, which requires renal replacement therapy such as at the time of registration at the Medawachchiya renal dialysis and transplantation. In 2005, 4.6% of the national clinic after screening in 2003. All the patients recruited for health budget (annual) was being spent on the management the cohort were followed up for 72 months from registra- of renal disease patients [9]. tion until 2009 or death. In this CKDu endemic region, an epidemiological sur- vey to evaluate the possible risk factors has revealed that a Baseline risk factor assessment family history of CKDu, taking ayurvedic treatment, and a history of snake bite are significant predictors for CKDu After registering the patients in the clinic, demographic occurrence [8]. As a result of the clinically observed het- and lifestyle-related information was collected by physi- erogeneity in disease progression, we hypothesized that the cians through face-to-face interviews using a structured rate of disease progression and death could be modified by questionnaire. If available, medical records were used to different demographic, clinical, and lifestyle-related fac- collect the relevant clinical information. The risk factors tors. To evaluate this, we followed up a CKDu cohort that of interest were: source of drinking water (agro-well, tube was identified in a high-risk population screening program, well, or garden well); habits (alcohol consumption, which is believed to be the first-ever cohort study of CKDu smoking, or betel chewing); family history of CKD, and in the NCP of Sri Lanka. It is expected that risk factor history of snake bites; frequently used medication; and identification will be crucial in the prevention of CKDu parental consanguinity. A history of hypertension, progression from mild to severe stages. malaria, or bed-wetting, and ultrasonographic findings of shrunken kidney were collected from medical records. The presence of dental fluorosis was recorded after Methods examination. Patients with mild hypertension (blood pressure \160/100 mmHg untreated, or \140/90 mmHg Cohort with up to two antihypertensive agents) were classified as hypertensive patients. If patients developed diabetes Target population screening programs using dipstick mellitus during the follow-up period, they were classified proteinuria were started in 2003 when there was a surge as diabetics. 123 Environ Health Prev Med (2012) 17:191–198 193 Covariates was categorized by sex and various age groups, using the SAS Statistical Package version 9.1 (SAS Institute, Cary, Body mass index NC, USA). After stratification by age and eGFR, sex/age adjusted hazard ratios (HRs) for CKDu were obtained The height and weight of the patients were measured in using a Cox proportional hazards model. The risk factors increments of 0.1 cm and 0.1 kg, respectively, while they considered in the analysis were: source of drinking water were wearing light clothing. Body mass index (BMI) was (agro-well, tube well, or garden well); habits (alcohol calculated as body weight (kg) divided by the square of consumption, smoking, or betel chewing); family history of height (m). BMI was categorized according to the World CKD; history of hypertension, malaria, bed-wetting, or Health Organization guidelines: \18.5 kg/m (under- snake bites; frequently used medication; parental consan- 2 2 weight), 18.5–24.9 kg/m (normal), 25–29.9 kg/m (over- guinity; and clinical findings (dental fluorosis, ultrasono- weight), and C30 kg/m (obese). graphic findings of shrunken kidney, BMI, serum creatinine levels, and CKDu stage at follow-up). In the first Serum creatinine and glomerular filtration rate trial of the Cox model, each factor was individually con- sidered (univariate Cox model), and age-corrected, sex- The latest serum creatinine level was used to calculate the stratified significant factors for disease progression were estimated glomerular filtration rate (eGFR) using the identified for CKDu stage 1–4 patients, using SAS (PROC Modified Diet in Renal Disease (MDRD) formula [10]: PHREG—outcome of the model was disease progression). Disease progression was determined according to the GFR ml=min=1:73m advance of CKDu stage over the monitoring period. In the 1:154 0:203 ¼ 186 ðÞ serum creatinine ðÞ Age second trial of the Cox model, all significant factors ðÞ 0:742 if femaleðÞ 1:233 : identified in the first analysis were combined (multivariate Cox model). Similar analysis was carried out for CKDu According to one of the most widely adopted classifica- stage 1 and stage 2–3 patients at the third and fourth Cox tions, proposed by the Kidney Disease Outcomes Quality model analyses for disease progression. Univariate and Initiative, five stages were defined for CKDu using the multivariate Cox model analyses (fifth and sixth Cox eGFR value [11]. If eGFR was C90 ml/min/1.73 m , but model analyses) were carried out to determine individual there was evidence of kidney damage such as proteinuria, and combined mortality factors. A Kaplan-Meier curve was patients were classified as CKDu stage 1. Stages 2–5 were generated with SAS soft ware. Log-rank and Wilcoxon classified according to eGFR values of 60–89, 30–59, tests were carried out to check the homogeneity of the 15–29, and \15 ml/min/1.73 m in stages 2, 3, 4, and 5, survival curves. All analyses were performed with the SAS respectively. Statistical Package version 9.1 (SAS Institute). This was a fact-finding study; therefore, we placed an emphasis on Kidney disease follow-up false-negative results. Thus, we considered p \ 0.10 as significant. For each member of the cohort, the person-years of follow- up were calculated from 2003 to the date of death or to the final year of the study period (2009). The entire cohort was Results closely monitored for 2 years (cohort established in 2003 and followed up in 2004 and 2005) for deaths and disease Study cohort progression, and then the patients were invited to partici- pate in the annual clinic to determine disease progression. The study cohort consisted of 143 patients with a mean age It was observed that 34 patients were missing in 2005 (SD) of 43 (6.5) years. They were predominantly Sinhalese without any records, and 81 were reported in 2006 and 76 in ethnicity (86%) and belonged to rural communities. The in 2007. Forty-four patients were reported in 2008, and in number of participants and their demographic characteris- 2009 only 25 were reported to the annual follow-up tics, BMI, and history of hypertension are shown in program. Table 1. Fifty-eight percent of the participants were men. Statistical analysis Importantly, the majority of the participants had low BMI (42%) and only 8% had high BMI (overweight and obese). Values for demographic variables, BMI, and history of The prevalence of hypertension was 24%, and 3% devel- hypertension in the study participants are presented as oped diabetes during the follow-up period. The distribution means with standard deviation (SD). MDRD-based eGFR of MDRD-estimated GFR categories by sex and age is 123 194 Environ Health Prev Med (2012) 17:191–198 Table 1 Distribution of demographic variables, BMI, and history of alcohol consumption, smoking, betel chewing, family his- hypertension among study participants in 2003 tory, hypertension, diabetes mellitus, malaria, bed-wetting, snake bites, medication used, parental consanguinity, All participants Number (%) Mean age (SD), years dental fluorosis, shrunken kidney, and BMI. Table 4 shows the significant factors obtained for disease progression for Women 60 (42) 38.42 (20.66) patients with stage 1–4 CKDu. Alcohol consumption, betel Men 83 (58) 47.66 (18.83) chewing, nonsteroidal anti-inflammatory drugs (NSAIDs), Age (years) and hypertension were identified as major individual fac- \20 24 (17) 13.6 (4.0) tors (age-adjusted and sex-stratified) for disease progres- 20–29 16 (11) 23.6 (2.9) sion, with HRs of 3.39, 3.61, 2.33, and 2.02, respectively 30–39 13 (9) 35.0 (3.3) (p \ 0.1). In the multivariate analysis with all significant 40–49 26 (18) 43.8 (3.0) factors, alcohol consumption and hypertension were the 50–59 30 (21) 53.8 (2.6) main factors for disease progression, with HRs of 3.64 60–69 20 (14) 64.0 (2.0) (p = 0.076) and 3.38 (p = 0.011), respectively. We repe- [70 14 (10) 76.6 (6.5) ated the same analysis for stage 1 and stage 2–3 patients, BMI (kg/m ) and the significant results are shown in Table 5. Hyper- \18.5 52 (42) 46.3 (23.0) tension was the only factor identified for disease progres- 18.5–24.9 62 (50) 44.4 (16.6) sion in stage 1 patients, with an HR of 7.29 (p = 0.34). 25–29.9 8 (6) 42.9 (11.5) Even though it was statistically not significant (p = 0.12), C30 2 (2) 31.0 (1.4) it is worth highlighting the factor of family history, with an Hypertension 34 (24) 54.1 (15.1) HR of 21.63. Hypertension, BMI, and malaria were iden- tified as the significant factors for disease progression in BMI body mass index (kg/m ), SD standard deviation stage 2 and 3 patients (sex-stratified and age-adjusted). presented in Table 2. The proportion of early-stage CKDu Hypertension showed the highest HR, of 3.07 (p = 0.060), patients was markedly reduced in the older age groups. For in this analysis. The dominance of hypertension was further example, in the youngest population (age \20 years), 92% emphasized by multivariate analysis, with an HR of 26.14 were CKDu stage 1 (GFR [90 ml/min/1.73 m ), but in the (p = 0.003); BMI and malaria showed lower HRs, of 0.64 older population (aged 60–69 years), the CKDu stage-1 (p = 0.011) and 0.27 (0.083), respectively. population was only 9%. In contrast, very few or no late- It was observed that hypertension repeatedly emerged as stage patients were found in the younger age group. For an important factor for disease progression, and we example, no patients were found in CKDu stage 4 (GFR developed Kaplan–Meier survival curves to illustrate this 15–29 ml/min/1.73 m ) in the younger age group further (Fig. 1). Different rank statistics tests were used to (\20 years), but almost 40% of the patients in the older age check the homogeneity of the survival curves. Log-rank group (60–69 years) were CKDu stage 4. and Wilcoxon tests showed v values of 11.4 (p = 0.0007) The cohort was closely monitored for 2 years for disease and 10.1 (p = 0.0014), respectively, which suggested a progression and death, and they were invited to join the comparatively rapid disease progression if the patients had annual monitoring program for another 4 years. The mean a history of hypertension in the early stages of the disease. period of observation was 39.9 months. It was found that In addition to hypertension, alcohol consumption and 11 patients died during the monitoring period of betel chewing were also identified as significant factors for 2003–2005, and the numbers of patients who came to the disease progression by univariate Cox model analysis, but follow-up clinics in 2005, 2006, 2007, 2008, and 2009 were in the multivariate analysis, their significance disappeared. 90, 81, 76, 44, and 25, respectively. Table 3 shows the However, it is noteworthy that in a previous study, by Chou number of deaths recorded during the first 2 years, cate- et al. [12], it was found that betel-nut use was associated gorized by CKDu stage and age (above and below with CKD in men and this association was independent of 65 years). The mortality rates in the present study were age, BMI, smoking, alcohol consumption, hypertension, compared with those reported in similar CKD cohort diabetes, and hyperlipidemia. studies from different parts of the world. Predictors of mortality Predictors of disease progression Univariate Cox survival analysis (age-adjusted and sex- A sex-stratified, age-adjusted, Cox proportional hazards stratified) suggested that hypertension, CKDu stage, and model was used to identify the individual parameters for shrunken kidney were the significant factors associated disease progression: occupation, drinking water source, with mortality rate, with HRs of 2.29 (p = 0.1), 3.00 123 Environ Health Prev Med (2012) 17:191–198 195 Table 2 MDRD-based GFR according to sex and age in 2003 Mean age (SD), years Total no. GFR (ml/min/1.73 m ) [90 60–89 30–59 15–29 \15 Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 All participants Women 38.42 (20.66) 60 24 (40.00) 11 (18.33) 14 (23.33) 9 (15.00) 2 (3.33) Men 47.66 (18.83) 83 26 (31.33) 11 (13.25) 18 (21.69) 14 (16.87) 14 (16.87) Age (years) \20 13.6 (4.0) 26 24 (92.30) 0 (0) 1 (3.87) 0 (0) 1 (3.83) 20–29 23.6 (2.9) 16 9 (56.25) 5 (31.25) 2 (12.50) 0 (0) 0 (0) 30–39 35.0 (3.3) 14 4 (28.57) 4 (28.57) 3 (21.43) 1 (7.14) 2 (14.29) 40–49 43.8 (3.0) 27 7 (25.93) 6 (22.22) 5 (18.52) 7 (25.93) 2 (7.41) 50–59 53.8 (2.6) 28 4 (14.29) 3 (10.17) 12 (42.86) 4 (14.29) 5 (17.86) 60–69 64.0 (2.0) 22 2 (9.09) 2 (9.09) 5 (22.73) 9 (40.91) 4 (18.18) [70 76.6 (6.5) 10 0 (0) 2 (20.00) 4 (40.00) 2 (20) 2 (20) Values are numbers (percentages) of participants unless stated otherwise GFR glomerular filtration rate (ml/min/1.73 m ), MDRD Modification of Diet in Renal Disease, SD standard deviation Table 3 CKDu cohort deaths during first 2 years follow-up (2004 \20 years old. In contrast, the proportion of CKD patients and 2005) aged \20 years in the United States is \2% [13]. Almost all the younger patients (\20 years) in this cohort had Age group (years) CKD stage Number (%) Observed deaths CKDu stage 1 and they comprised 24% of the stage-1 \65 1 and 2 51 (53.13) 0 population. Therefore, it is reasonable to presume that the 3 20 (20.83) 1 problem will become much more serious in the coming few 4 16 (16.67) 3 decades when these patients progress to late stages of the 5 9 (9.34) 4 disease. Even though the older age group ([70 years) Total 96 8 comprises 37% of the CKD population in the United States [65 1 and 2 4 (30.77) 0 [13], only about 10% of the patients in our cohort were 3 4 (30.77) 0 [70 years old. 4 2 (15.38) 1 A similar age-structure pyramid in the CKD population 5 3 (23.08) 2 has been reported from another Asian country, Iran, where Total 13 3 23.6% are aged \30 years, and only 6.0% are [70 years old [4]. In the present cohort, 37% of stage 3–5 CKDu Values are numbers (percentages) of participants unless stated otherwise patients were older than 60 years. CKDu chronic kidney disease of uncertain etiology In our cohort, the probability of death in a 2-year period was 23% for a patient older than 65 years and that was 8% (p = 0.00), and 2.74 (p = 0.09), respectively (Table 4). In for a patient younger than 66 years. These values are multivariate Cox survival analysis, the dominance of almost double those reported by Manns et al. [14], who CKDu stage was observed over other significant factors, showed that the probability of death in a CKD cohort in with an HR of 2.94 (p = 0.001). Alberta, Canada, was 4.81% for patients aged \66 years and 13.29% for those aged [65 years. It is particularly interesting to note that 81% of the Canadian cohort had Discussion CKD stage 1 or 2, 18% had stage 3, and 1% had stage 4 or 5, whereas in our cohort, 50% had stage 1 or 2, 22% had This study is believed to be the first to identify possible risk stage 3, and 28% had stage 4 or 5. This demonstrated that factors of CKDu disease progression and death in a pro- the disease progression in our CKDu cohort was much spective cohort in Madawachchiya, Sri Lanka, where faster than that in western countries, and we suspect that CKDu is endemic. this could be a reason for the higher death rate in our The age-structure pyramid of this CKDu cohort was cohort. The overall death rate in our cohort was 5.3% per broad-based, with a relatively large proportion of younger 100 patient-years, which is higher than the rate reported in patients. For example, 17% of the CKDu patients were Taiwan [15]. Lack of adequate dialysis facilities to manage 123 196 Environ Health Prev Med (2012) 17:191–198 Table 4 Sex-stratified, age-adjusted univariate and multivariate Cox proportional models for CKDu disease progression and death Outcome Type of analysis Variable Hazard 95% Confidence p value ratio interval Disease progression Sex-stratified, age-adjusted univariate analysis Alcohol 3.39 1.43–8.04 0.006 (CKD stage 1–4) Betel 3.61 1.21–10.77 0.021 Hypertension 2.02 0.09–45.34 0.907 NSAID 2.33 0.95–5.71 0.065 Sex-stratified, age-adjusted multivariate Alcohol 3.64 0.87–15.23 0.076 (alcohol, betel, hypertension, NSAID) Betel 1.94 0.52–7.24 0.325 analysis Hypertension 3.38 1.31–8.72 0.011 NSAID 1.28 0.42–3.90 0.662 Death (CKD stage 1–5) Sex-stratified, age-adjusted univariate analysis Hypertension 2.29 0.85–6.17 0.100 CKD stage 3.00 1.71–5.26 0.000 Shrunken kidney 2.74 0.83–9.05 0.097 Sex-stratified, age-adjusted multivariate Hypertension 1.79 0.62–5.17 0.277 (hypertension, CKD stage, shrunken kidney) CKD stage 2.94 1.57–5.51 0.001 analysis Shrunken kidney 0.80 0.21–3.05 0.742 NSAID nonsteroidal anti-inflammatory drug, CKDu chronic kidney disease of uncertain etiology, Betel betel chewing, Alcohol alcohol consumption Table 5 Sex-stratified, age-adjusted univariate and multivariate Cox proportional models of disease progression for stage-specific analysis CKDu Type of analysis Variable Hazard ratio 95% Confidence p value interval Stage 1 Sex-stratified, age-adjusted univariate analysis Hypertension 7.29 1.16–45.81 0.034 Family history 21.63 0.44–1063.31 0.120 Stage 2–3 Sex-stratified, age-adjusted univariate analysis Hypertension 3.07 0.95–9.92 0.060 BMI 0.85 0.72–1.00 0.070 Malaria 0.26 0.08–0.85 0.027 Sex-stratified, age-adjusted multivariate (hypertension, Hypertension 26.14 3.04–224.77 0.003 BMI, malaria) analysis BMI 0.64 0.45–0.91 0.011 Malaria 0.27 0.06–1.22 0.083 BMI body mass index (kg/m ), CKDu chronic kidney disease of uncertain etiology the CKDu patients in this region might have contributed to affected population was male. However, the majority of this higher mortality. published studies have shown female-dominant CKD BMI is associated with CKD [16, 17]. Many researchers cohorts [4, 22, 23]. Further research is needed to determine have reported that higher BMI is a risk factor for CKD in the reasons for male dominance in our study area. How- apparently healthy persons [18, 19]. By contrast, in our ever, factors such as genetic susceptibility and some cohort, only 8% of the patients were overweight behavioral risk factors, such as alcohol consumption and 2 2 (25–29.9 kg/m ) or obese ([30 kg/m ), whereas 42% of betel chewing, which could play a role in increasing dis- the patients were underweight (\18.5 kg/m ). According to ease occurrence, should not be neglected. some studies, malnutrition has been shown to increase Diabetes and hypertension are known risk factors for mortality risk more than high BMI [20, 21], and malnu- CKD [24, 25]. According to the definition of CKDu, trition could have also contributed to the higher death rate patients with diabetes and uncontrollable hypertension in our cohort. were not included in the present cohort. However, it should In our study, men (58%) were at higher risk of CKDu be noted that five patients developed diabetes and several than women were (42%). A similar association has been developed hypertension during the follow-up period. At the reported in a study in Taiwan [15], where 62% of the same time, several patients had mild hypertension at the 123 Environ Health Prev Med (2012) 17:191–198 197 common in the older age groups [30]. In the elderly pop- ulation, eGFR is reduced in the normal aging process, but elderly patients have a greater mortality risk when com- pared with younger patients with the same eGFR range [30]. Therefore, it is likely that elderly patients will die in the middle of the disease process rather than reaching the end stage of CKD. However, our CKDu cohort was rela- tively younger than the cohorts that have been studied in other countries [15, 24, 25]. Thus, we can imagine that these CKDu patients would survive until they reach end- stage CKD, in contrast to the population who are already in the latter part of their life when they begin the disease process. Our study had a number of limitations. The study was started at the initiation of community screening in this endemic area; therefore, we could recruit only a limited number of patients. We used the MDRD formula for esti- Fig. 1 Kaplan–Meier curves showing the probability of chronic kidney disease of uncertain etiology (CKDu) disease progression over mation for GFR, which has not been validated for the Sri the monitoring period with and without self-reported hypertension for Lankan population and across the age range. Therefore, the CKDu stage 1 (glomerular filtration rate [GFR] [90 ml/min/1.73 m ) use of eGFR for staging the patients might not have patients (please refer to the ‘‘Results’’ section in the text for Log-rank reflected the actual GFR for this population. For the test and Wilcoxon test results) exclusion of diabetes mellitus, we used a cut-off HbA1C level of 6.5%. However, previous studies have shown that time of diagnosis of CKDu. Among the factors that were such a cut-off level misses a substantial number of people evaluated as suspected risk factors for disease progression with type 2 diabetes, including some with fasting hyper- in our cohort, hypertension was identified as the leading glycemia, as well as people with impaired glucose toler- determinant of disease progression. Self-reported hyper- ance [31]. Therefore, there is a possibility that we might tension was a significant predictor (p \ 0.05) for disease have recruited some diabetic patients in this cohort because progression, with an HR of 3.38 by multivariate Cox pro- of misdiagnosis. portional model analysis for stage 1–4 patients. Our results suggest a strong correlation between hypertension in the early stage of CKDu and disease progression. Sixty-six Conclusions percent of stage 1 patients in our cohort were from the population aged \30 years, and hypertension showed an In this study, we tried to determine factors possibly asso- HR of 7.26 in a sex-stratified, age-adjusted Cox propor- ciated with progression and mortality of CKDu in a single- tional model for stage 1 patients. A similar correlation was center cohort registered in the Medawachchiya regional observed for stage 2–3 patients, with an HR of 26.16. Many clinic in Sri Lanka. We repeatedly found an association researchers have shown that the prevalence of hypertension between disease progression and hypertension. Men were in South Asian populations is higher than that in western at higher risk of CKDu than women. A significant pro- populations [26]. These results strongly suggest that tight portion of the patients in this cohort were underweight, control of blood pressure, particularly in the early stage of indicating a need for future studies on the nutritional status CKDu, has a beneficial effect to slow down disease of these patients. Compared with findings in western progression. countries and other regions of Asia, younger age at disease CKDu stage was the only factor identified to have a onset, equal patient distribution in different age groups, correlation with death, with HRs of 3.0 and 2.94 by uni- faster disease progression in those with hypertension, variate (sex-stratified and age-adjusted) and multivariate deaths occurring mostly in end-stage CKDu, and relatively Cox proportional model analysis, respectively. This result higher mortality rate are some of the characteristics that is supported by the fact that almost all reported deaths were were identified in this cohort. in patients with stage 4 or 5 disease. In contrast, many Acknowledgments The authors would like to thank Dr. Arjuna studies have reported that CKD patients in western coun- Dandeniya, Dr. Gayan Wijesundara, and Dr. Amila Kodikara; the tries frequently die before developing end-stage CKD [27– temporary lecturers of the Department of Pharmacology, Faculty of 29]. The reason for this could be the difference in age at Medicine, University of Peradeniya, Sri Lanka, for their support in disease initiation, because in many countries, CKD is data handling. This study was supported by the Special Coordination 123 198 Environ Health Prev Med (2012) 17:191–198 Funds for Promoting Science and Technology from the Ministry of 13. United States Renal Data System (USRDS) Annual data report Education, Culture, Sports, Science and Technology in Japan. The 2010. http://www.usrds.org/ funding agency had no role in the study design, data collection, and 14. Manns B, Hemmelgarn B, Tonelli M, Au F, Hiasson C, Dong J, analysis, or in the decision to publish or in the preparation of the Klarenbach C. Population based screening for chronic kidney manuscript. TA, EM, and AK conceived and designed the experi- disease: cost effectiveness study. BMJ. 2010;341:c5869. ments. TA and RC performed the experiments. STMLDS, SN, KHH 15. Chiu Y, Chien K, Lin S, Chen Y, Tsai T, Wu D. Outcomes of and TH statistically analyzed the data. STMLDS, SN, KHH, and AK stage 3–5 chronic kidney disease before end-stage renal disease at wrote the paper. NR, TK, EM, and AK critically revised the draft. All a single center in Taiwan. Nephron Clin Pract. 2008;109: authors read and approved the manuscript. c109–18. 16. Nomura I, Kato J, Kitamura K. Association between body mass Conflict of interest The authors declare that they have no com- index and chronic kidney disease: a population-based, cross- peting interests. sectional study of a Japanese community. Vasc Health Risk Manag. 2009;5:315–20. 17. Chalmers L, Kaskel FJ, Bamgbola O. The role of obesity and its bioclinical correlates in the progression of chronic kidney dis- ease. Adv Chronic Kidney Dis. 2006;13(4):352–64. 18. Hsu CY, McCulloch CE, Iribarren C, Darbinian J, Go AS. Body References mass index and risk for end-stage renal disease. Ann Intern Med. 2006;144:21–8. 19. Gelber RP, Kurth T, Kausz AT, Manson JE, Buring JE, Levey 1. Hwang SJ, Tsai JC, Chen HC. Epidemiology, impact and pre- AS, Gaziano JM. Association between body mass index and CKD ventive care of chronic kidney disease in Taiwan. Nephrology in apparently healthy men. Am J Kidney Dis. 2005;46:871–80. (Carlton). 2010;15(2):3–9. 20. Beddhu S. The body mass index paradox and an obesity, 2. Perlman RL, Finkelstein FO, Liu L, Roys E, Kiser M, Eisele G, inflammation, and atherosclerosis syndrome in chronic kidney Burrows-Hudson S, Messana JM, Levin N, Rajagopalan S, Port disease. Semin Dialysis. 2004;17:229–32. FK, Wolfe RA, Saran R. Quality of life in Chronic Kidney 21. Kalantar-Zadeh K, Block G, Humphreys MH, Kopple JD. Disease (CKD): a cross-sectional analysis in the Renal Research Reverse epidemiology of cardiovascular risk factors in mainte- Institute-CKD study. Am J Kidney Dis. 2005;45(4):658–66. nance dialysis patients. Kidney Int. 2003;63:793–808. 3. Menon V, Sarnak MJ. The epidemiology of chronic kidney dis- 22. Zhang QL, Rothenbacher D. Prevalence of chronic kidney dis- ease stages 1 to 4 and cardiovascular disease: a high-risk com- ease in population-based studies: systematic review. BMC Public bination. Am J Kidney Dis. 2005;45(1):223–32. Health. 2008;8:117. 4. Najafi I, Attari F, Islami F, Shakeri R, Malekzadeh F, Salahi R, 23. Ong-Ajyooth L, Vareesangthip K, Khonputsa P, Aekplakorn W. Gharavi MY, Hosseini M, Broumand B, Haghighi AN, Larijani Prevalence of chronic kidney disease in Thai adults: a national B, Malekzadeh R. Renal function and risk factors of moderate to health survey. BMC Nephrol. 2009;10:35. severe chronic kidney disease in Golestan Province, northeast of 24. Coresh J, Astor BC, Greene T, Eknoyan G, Levey AS. Prevalence Iran. PLoS One. 2010;5(12):e14216. of chronic kidney disease and decreased kidney function in the 5. Brown WW, Peters RM, Ohmit SE, Keane WF, Collins A, Chen adult US population: Third National Health and Nutrition SC, King K, Klag MJ, Molony DA, Flack JM. Early detection of Examination Survey. Am J Kidney Dis. 2003;41:1–12. kidney disease in community settings: the Kidney Early Evalu- 25. Chen J, Wildman RP, Gu D, Kusek JW, Spruill M. Prevalence of ation Program (KEEP). Am J Kidney Dis. 2003;42:22–35. decreased kidney function in Chinese adults aged 35 to 74 years. 6. Ayodele OE, Alebiosu CO. Burden of chronic kidney disease: an Kidney Int. 2005;68:2837–45. international perspective. Adv Chronic Kidney Dis. 2010;17(3): 26. Jones CA, Mawani S, King KM, Allu SO, Smith M, Mohan S, 215–24. Campbell NRC. Tackling health literacy: adaptation of public 7. Chandrajith R, Nanayakkara S, Itai K, Aturaliya TN, Dissanayake hypertension educational materials for an Indo-Asian population CB, Abeysekara T, Harada K, Watanabe T, Koizumi A. Chronic in Canada. BMC Public Health. 2011;11(1):24. kidney disease of uncertain aetiology (CKDue) in Sri Lanka: 27. Adler AI, Stevens RJ, Manley SE, Bilous RW, Cull CA, Holman geographic distribution and environmental implications. Environ RR. Development and progression of nephropathy in type 2 Geochem Health. 2011;409(11):671–5. diabetes: the United Kingdom Prospective Diabetes Study 8. Wanigasuriya KP, Peiris-John RJ, Wickremasinghe R, Hittarage (UKPDS 64). Kidney Int. 2003;63:225–32. A. Chronic renal failure in North Central Province of Sri Lanka: 28. Kovesdy CP, Trivedi BK, Anderson JE. Association of kidney an environmentally induced disease. Trans R Soc Trop Med Hyg. function with mortality in patients with chronic kidney disease 2007;101:1013–7. not yet on dialysis: a historical prospective cohort study. Adv 9. World Health Organization (WHO) country office Sri Lanka- Chronic Kidney Dis. 2006;13:183–8. News letters. http://www.whosrilanka.org/EN/Section1_76.htm 29. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic Accessed 10 Dec 2010. kidney disease and the risks of death, cardiovascular events, and 10. Levey AS, Bosch JP, Lewis JB, Modification of Diet in Renal hospitalization. N Engl J Med. 2004;351:1296–305. Disease Study Group. A more accurate method to estimate glo- merular filtration rate from serum creatinine: a new prediction 30. O’Hare AM, Choi AI, Bertenthal D, Bacchetti P, Garg AX, Ka- equation. Ann Intern Med. 1999;130:461–70. ufman JS, Walter LC, Mehta KM, Steinman MA, Allon M, McClellan WM, Landefeld CS. Age affects outcomes in chronic 11. The National Kidney Foundation. K/DOQI Clinical practice kidney disease. J Am Soc Nephrol. 2007;18:2758–65. guidelines for chronic kidney disease: evaluation, classification, 31. Herman WH, Fajans SS. Hemoglobin A1c for the diagnosis of and stratification. Am J Kidney Dis. 2002;39:S46–75. diabetes: practical considerations. Pol Arch Med Wewn. 12. Chou CY, Cheng SY, Liu JH, Cheng WC, Kang IM, Tseng YH, Shih 2010;120(1–2):37–40. CM, Chen W. Association between betel-nut chewing and chronic kidney disease in men. Public Health Nutr. 2009;12(5):723–7. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Environmental Health and Preventive Medicine Springer Journals

Risk factors associated with disease progression and mortality in chronic kidney disease of uncertain etiology: a cohort study in Medawachchiya, Sri Lanka

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Springer Journals
Copyright
Copyright © 2011 by The Japanese Society for Hygiene
Subject
Medicine & Public Health; Health Promotion and Disease Prevention; Public Health
ISSN
1342-078X
eISSN
1347-4715
DOI
10.1007/s12199-011-0237-7
pmid
21881957
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Abstract

Environ Health Prev Med (2012) 17:191–198 DOI 10.1007/s12199-011-0237-7 REGULAR A R T IC LE Risk factors associated with disease progression and mortality in chronic kidney disease of uncertain etiology: a cohort study in Medawachchiya, Sri Lanka • • • Lalantha Senevirathna Tilak Abeysekera Shanika Nanayakkara • • • Rohana Chandrajith Neelakanthi Ratnatunga Kouji H. Harada • • • Toshiaki Hitomi Toshiyuki Komiya Eri Muso Akio Koizumi Received: 11 July 2011 / Accepted: 8 August 2011 / Published online: 1 September 2011 The Japanese Society for Hygiene 2011 Abstract Methods This study sought to determine the possible fac- Background The alarming rise in the prevalence of tors associated with the progression and mortality of CKDu. chronic kidney disease of uncertain etiology (CKDu) The study utilized a single-center cohort registered in 2003 among the low socioeconomic farming community in the and followed up until 2009 in a regional clinic in the endemic North Central Province of Sri Lanka has been recognized region, and used a Cox proportional hazards model. as an emerging public health issue in the country. Results We repeatedly found an association between disease progression and hypertension. Men were at higher risk of CKDu than women. A significant proportion of the patients in this cohort were underweight, which empha- For the Chronic Kidney Disease of Uncertain Aetiology Consortium. sized the need for future studies on the nutritional status of A full list of Consortium members is provided in additional file 1 these patients. in the electronic supplementary material. Conclusions Compared with findings in western countries and other regions of Asia, we identified hypertension as a L. Senevirathna, T. Abeysekera, and S. Nanayakkara contributed major risk factor for progression of CKDu in this cohort. equally to this work. Electronic supplementary material The online version of this Keywords Chronic kidney disease of uncertain etiology article (doi:10.1007/s12199-011-0237-7) contains supplementary Progression  Hypertension  Sri Lanka material, which is available to authorized users. L. Senevirathna  S. Nanayakkara  K. H. Harada R. Chandrajith T. Hitomi  A. Koizumi (&) Department of Geology, Faculty of Science, Department of Health and Environmental Sciences, University of Peradeniya, Peradeniya, Sri Lanka Kyoto University Graduate School of Medicine, e-mail: rohanac@hotmail.com Kyoto, Japan e-mail: koizumi.akio.5v@kyoto-u.ac.jp N. Ratnatunga Department of Pathology, Faculty of Medicine, L. Senevirathna University of Peradeniya, Peradeniya, Sri Lanka e-mail: lalantha.s@kt3.ecs.kyoto-u.ac.jp e-mail: neela72002@yahoo.com S. Nanayakkara e-mail: shanika.n@at2.ecs.kyoto-u.ac.jp T. Komiya  E. Muso Department of Nephrology and Dialysis, Kitano Hospital, K. H. Harada Tazuke Kofukai Medical Research Institute, Osaka, Japan e-mail: harada.koji.3w@kyoto-u.ac.jp e-mail: t-komiya@kitano-hp.or.jp T. Hitomi E. Muso e-mail: hitomi.t@ax4.ecs.kyoto-u.ac.jp e-mail: muso@kitano-hp.or.jp T. Abeysekera Nephrology Unit, General Hospital (Teaching), Kandy, Sri Lanka e-mail: tilak_1@hotmail.com 123 192 Environ Health Prev Med (2012) 17:191–198 Introduction in new registrations with CKDu in the local renal clinics in the NCP. Early-morning urine samples from people Chronic kidney disease (CKD) has emerged as a global aged [5 years (except for menstruating women) were public health issue [1] and has become an important cause checked on three occasions, with an interval of 1 week of morbidity and mortality [2]. Patients with CKD consti- between consecutive samples. Subjects with proteinuria tute a significant economic burden, both directly in terms on two or more occasions were referred to renal clinics of resource utilization, and indirectly through loss of for further confirmatory investigations. Patients with productivity and impaired quality of life [3]. In the past CKDu were diagnosed after excluding known etiologies. decade, 1.1 trillion dollars have been spent on dialysis Diabetes mellitus was excluded by the absence of a worldwide [4]. Therefore, early detection of asymptomatic history, no current treatment, and hemoglobin A1C CKD patients is important because early intervention has a (HbA1C) \6.5%. Malignant hypertension was excluded reasonable chance of making a positive impact on outcome by the absence of a history of chronic and/or severe [5]. Similarly, it is important to prevent or delay disease hypertension. If blood pressure was \160/100 mmHg progression from mild to severe stages [4]. The global untreated or \140/90 mmHg with up to two antihyper- increase in the prevalence of CKD and its disproportionate tensive agents, those people were included in the CKDu burden on economically developing countries is being group. Systemic lupus erythematosus was excluded by driven by an increase in the prevalence of the main risk the absence of anti-nuclear factor and double-stranded factors for CKD; namely, diabetes, hypertension, obesity, DNA antibody. In all cases, biopsy was conducted for and aging of the population [6]. pathological diagnosis. CKDu was pathologically defined However, in the North Central Province (NCP) of Sri as a region of focal-to-diffuse interstitial fibrosis and Lanka, the dramatically increasing prevalence of CKD tubular atrophy. IgA nephropathy was excluded by during the past two decades has not been attributable to any immunostaining for IgG, IgM, IgA, and complement of these factors [7]. Thus, it has been named CKD of component C3. Urological diseases of known etiology uncertain etiology (CKDu). The majority of CKDu patients were excluded by clinical symptoms and routine in the NCP are from the low socioeconomic farming investigations. community [8]. As a result of the insidious onset and All patients who were diagnosed with CKDu were progression of the disease, these patients present in the late registered in local clinics. We recruited 143 CKDu patients stages, which requires renal replacement therapy such as at the time of registration at the Medawachchiya renal dialysis and transplantation. In 2005, 4.6% of the national clinic after screening in 2003. All the patients recruited for health budget (annual) was being spent on the management the cohort were followed up for 72 months from registra- of renal disease patients [9]. tion until 2009 or death. In this CKDu endemic region, an epidemiological sur- vey to evaluate the possible risk factors has revealed that a Baseline risk factor assessment family history of CKDu, taking ayurvedic treatment, and a history of snake bite are significant predictors for CKDu After registering the patients in the clinic, demographic occurrence [8]. As a result of the clinically observed het- and lifestyle-related information was collected by physi- erogeneity in disease progression, we hypothesized that the cians through face-to-face interviews using a structured rate of disease progression and death could be modified by questionnaire. If available, medical records were used to different demographic, clinical, and lifestyle-related fac- collect the relevant clinical information. The risk factors tors. To evaluate this, we followed up a CKDu cohort that of interest were: source of drinking water (agro-well, tube was identified in a high-risk population screening program, well, or garden well); habits (alcohol consumption, which is believed to be the first-ever cohort study of CKDu smoking, or betel chewing); family history of CKD, and in the NCP of Sri Lanka. It is expected that risk factor history of snake bites; frequently used medication; and identification will be crucial in the prevention of CKDu parental consanguinity. A history of hypertension, progression from mild to severe stages. malaria, or bed-wetting, and ultrasonographic findings of shrunken kidney were collected from medical records. The presence of dental fluorosis was recorded after Methods examination. Patients with mild hypertension (blood pressure \160/100 mmHg untreated, or \140/90 mmHg Cohort with up to two antihypertensive agents) were classified as hypertensive patients. If patients developed diabetes Target population screening programs using dipstick mellitus during the follow-up period, they were classified proteinuria were started in 2003 when there was a surge as diabetics. 123 Environ Health Prev Med (2012) 17:191–198 193 Covariates was categorized by sex and various age groups, using the SAS Statistical Package version 9.1 (SAS Institute, Cary, Body mass index NC, USA). After stratification by age and eGFR, sex/age adjusted hazard ratios (HRs) for CKDu were obtained The height and weight of the patients were measured in using a Cox proportional hazards model. The risk factors increments of 0.1 cm and 0.1 kg, respectively, while they considered in the analysis were: source of drinking water were wearing light clothing. Body mass index (BMI) was (agro-well, tube well, or garden well); habits (alcohol calculated as body weight (kg) divided by the square of consumption, smoking, or betel chewing); family history of height (m). BMI was categorized according to the World CKD; history of hypertension, malaria, bed-wetting, or Health Organization guidelines: \18.5 kg/m (under- snake bites; frequently used medication; parental consan- 2 2 weight), 18.5–24.9 kg/m (normal), 25–29.9 kg/m (over- guinity; and clinical findings (dental fluorosis, ultrasono- weight), and C30 kg/m (obese). graphic findings of shrunken kidney, BMI, serum creatinine levels, and CKDu stage at follow-up). In the first Serum creatinine and glomerular filtration rate trial of the Cox model, each factor was individually con- sidered (univariate Cox model), and age-corrected, sex- The latest serum creatinine level was used to calculate the stratified significant factors for disease progression were estimated glomerular filtration rate (eGFR) using the identified for CKDu stage 1–4 patients, using SAS (PROC Modified Diet in Renal Disease (MDRD) formula [10]: PHREG—outcome of the model was disease progression). Disease progression was determined according to the GFR ml=min=1:73m advance of CKDu stage over the monitoring period. In the 1:154 0:203 ¼ 186 ðÞ serum creatinine ðÞ Age second trial of the Cox model, all significant factors ðÞ 0:742 if femaleðÞ 1:233 : identified in the first analysis were combined (multivariate Cox model). Similar analysis was carried out for CKDu According to one of the most widely adopted classifica- stage 1 and stage 2–3 patients at the third and fourth Cox tions, proposed by the Kidney Disease Outcomes Quality model analyses for disease progression. Univariate and Initiative, five stages were defined for CKDu using the multivariate Cox model analyses (fifth and sixth Cox eGFR value [11]. If eGFR was C90 ml/min/1.73 m , but model analyses) were carried out to determine individual there was evidence of kidney damage such as proteinuria, and combined mortality factors. A Kaplan-Meier curve was patients were classified as CKDu stage 1. Stages 2–5 were generated with SAS soft ware. Log-rank and Wilcoxon classified according to eGFR values of 60–89, 30–59, tests were carried out to check the homogeneity of the 15–29, and \15 ml/min/1.73 m in stages 2, 3, 4, and 5, survival curves. All analyses were performed with the SAS respectively. Statistical Package version 9.1 (SAS Institute). This was a fact-finding study; therefore, we placed an emphasis on Kidney disease follow-up false-negative results. Thus, we considered p \ 0.10 as significant. For each member of the cohort, the person-years of follow- up were calculated from 2003 to the date of death or to the final year of the study period (2009). The entire cohort was Results closely monitored for 2 years (cohort established in 2003 and followed up in 2004 and 2005) for deaths and disease Study cohort progression, and then the patients were invited to partici- pate in the annual clinic to determine disease progression. The study cohort consisted of 143 patients with a mean age It was observed that 34 patients were missing in 2005 (SD) of 43 (6.5) years. They were predominantly Sinhalese without any records, and 81 were reported in 2006 and 76 in ethnicity (86%) and belonged to rural communities. The in 2007. Forty-four patients were reported in 2008, and in number of participants and their demographic characteris- 2009 only 25 were reported to the annual follow-up tics, BMI, and history of hypertension are shown in program. Table 1. Fifty-eight percent of the participants were men. Statistical analysis Importantly, the majority of the participants had low BMI (42%) and only 8% had high BMI (overweight and obese). Values for demographic variables, BMI, and history of The prevalence of hypertension was 24%, and 3% devel- hypertension in the study participants are presented as oped diabetes during the follow-up period. The distribution means with standard deviation (SD). MDRD-based eGFR of MDRD-estimated GFR categories by sex and age is 123 194 Environ Health Prev Med (2012) 17:191–198 Table 1 Distribution of demographic variables, BMI, and history of alcohol consumption, smoking, betel chewing, family his- hypertension among study participants in 2003 tory, hypertension, diabetes mellitus, malaria, bed-wetting, snake bites, medication used, parental consanguinity, All participants Number (%) Mean age (SD), years dental fluorosis, shrunken kidney, and BMI. Table 4 shows the significant factors obtained for disease progression for Women 60 (42) 38.42 (20.66) patients with stage 1–4 CKDu. Alcohol consumption, betel Men 83 (58) 47.66 (18.83) chewing, nonsteroidal anti-inflammatory drugs (NSAIDs), Age (years) and hypertension were identified as major individual fac- \20 24 (17) 13.6 (4.0) tors (age-adjusted and sex-stratified) for disease progres- 20–29 16 (11) 23.6 (2.9) sion, with HRs of 3.39, 3.61, 2.33, and 2.02, respectively 30–39 13 (9) 35.0 (3.3) (p \ 0.1). In the multivariate analysis with all significant 40–49 26 (18) 43.8 (3.0) factors, alcohol consumption and hypertension were the 50–59 30 (21) 53.8 (2.6) main factors for disease progression, with HRs of 3.64 60–69 20 (14) 64.0 (2.0) (p = 0.076) and 3.38 (p = 0.011), respectively. We repe- [70 14 (10) 76.6 (6.5) ated the same analysis for stage 1 and stage 2–3 patients, BMI (kg/m ) and the significant results are shown in Table 5. Hyper- \18.5 52 (42) 46.3 (23.0) tension was the only factor identified for disease progres- 18.5–24.9 62 (50) 44.4 (16.6) sion in stage 1 patients, with an HR of 7.29 (p = 0.34). 25–29.9 8 (6) 42.9 (11.5) Even though it was statistically not significant (p = 0.12), C30 2 (2) 31.0 (1.4) it is worth highlighting the factor of family history, with an Hypertension 34 (24) 54.1 (15.1) HR of 21.63. Hypertension, BMI, and malaria were iden- tified as the significant factors for disease progression in BMI body mass index (kg/m ), SD standard deviation stage 2 and 3 patients (sex-stratified and age-adjusted). presented in Table 2. The proportion of early-stage CKDu Hypertension showed the highest HR, of 3.07 (p = 0.060), patients was markedly reduced in the older age groups. For in this analysis. The dominance of hypertension was further example, in the youngest population (age \20 years), 92% emphasized by multivariate analysis, with an HR of 26.14 were CKDu stage 1 (GFR [90 ml/min/1.73 m ), but in the (p = 0.003); BMI and malaria showed lower HRs, of 0.64 older population (aged 60–69 years), the CKDu stage-1 (p = 0.011) and 0.27 (0.083), respectively. population was only 9%. In contrast, very few or no late- It was observed that hypertension repeatedly emerged as stage patients were found in the younger age group. For an important factor for disease progression, and we example, no patients were found in CKDu stage 4 (GFR developed Kaplan–Meier survival curves to illustrate this 15–29 ml/min/1.73 m ) in the younger age group further (Fig. 1). Different rank statistics tests were used to (\20 years), but almost 40% of the patients in the older age check the homogeneity of the survival curves. Log-rank group (60–69 years) were CKDu stage 4. and Wilcoxon tests showed v values of 11.4 (p = 0.0007) The cohort was closely monitored for 2 years for disease and 10.1 (p = 0.0014), respectively, which suggested a progression and death, and they were invited to join the comparatively rapid disease progression if the patients had annual monitoring program for another 4 years. The mean a history of hypertension in the early stages of the disease. period of observation was 39.9 months. It was found that In addition to hypertension, alcohol consumption and 11 patients died during the monitoring period of betel chewing were also identified as significant factors for 2003–2005, and the numbers of patients who came to the disease progression by univariate Cox model analysis, but follow-up clinics in 2005, 2006, 2007, 2008, and 2009 were in the multivariate analysis, their significance disappeared. 90, 81, 76, 44, and 25, respectively. Table 3 shows the However, it is noteworthy that in a previous study, by Chou number of deaths recorded during the first 2 years, cate- et al. [12], it was found that betel-nut use was associated gorized by CKDu stage and age (above and below with CKD in men and this association was independent of 65 years). The mortality rates in the present study were age, BMI, smoking, alcohol consumption, hypertension, compared with those reported in similar CKD cohort diabetes, and hyperlipidemia. studies from different parts of the world. Predictors of mortality Predictors of disease progression Univariate Cox survival analysis (age-adjusted and sex- A sex-stratified, age-adjusted, Cox proportional hazards stratified) suggested that hypertension, CKDu stage, and model was used to identify the individual parameters for shrunken kidney were the significant factors associated disease progression: occupation, drinking water source, with mortality rate, with HRs of 2.29 (p = 0.1), 3.00 123 Environ Health Prev Med (2012) 17:191–198 195 Table 2 MDRD-based GFR according to sex and age in 2003 Mean age (SD), years Total no. GFR (ml/min/1.73 m ) [90 60–89 30–59 15–29 \15 Stage 1 Stage 2 Stage 3 Stage 4 Stage 5 All participants Women 38.42 (20.66) 60 24 (40.00) 11 (18.33) 14 (23.33) 9 (15.00) 2 (3.33) Men 47.66 (18.83) 83 26 (31.33) 11 (13.25) 18 (21.69) 14 (16.87) 14 (16.87) Age (years) \20 13.6 (4.0) 26 24 (92.30) 0 (0) 1 (3.87) 0 (0) 1 (3.83) 20–29 23.6 (2.9) 16 9 (56.25) 5 (31.25) 2 (12.50) 0 (0) 0 (0) 30–39 35.0 (3.3) 14 4 (28.57) 4 (28.57) 3 (21.43) 1 (7.14) 2 (14.29) 40–49 43.8 (3.0) 27 7 (25.93) 6 (22.22) 5 (18.52) 7 (25.93) 2 (7.41) 50–59 53.8 (2.6) 28 4 (14.29) 3 (10.17) 12 (42.86) 4 (14.29) 5 (17.86) 60–69 64.0 (2.0) 22 2 (9.09) 2 (9.09) 5 (22.73) 9 (40.91) 4 (18.18) [70 76.6 (6.5) 10 0 (0) 2 (20.00) 4 (40.00) 2 (20) 2 (20) Values are numbers (percentages) of participants unless stated otherwise GFR glomerular filtration rate (ml/min/1.73 m ), MDRD Modification of Diet in Renal Disease, SD standard deviation Table 3 CKDu cohort deaths during first 2 years follow-up (2004 \20 years old. In contrast, the proportion of CKD patients and 2005) aged \20 years in the United States is \2% [13]. Almost all the younger patients (\20 years) in this cohort had Age group (years) CKD stage Number (%) Observed deaths CKDu stage 1 and they comprised 24% of the stage-1 \65 1 and 2 51 (53.13) 0 population. Therefore, it is reasonable to presume that the 3 20 (20.83) 1 problem will become much more serious in the coming few 4 16 (16.67) 3 decades when these patients progress to late stages of the 5 9 (9.34) 4 disease. Even though the older age group ([70 years) Total 96 8 comprises 37% of the CKD population in the United States [65 1 and 2 4 (30.77) 0 [13], only about 10% of the patients in our cohort were 3 4 (30.77) 0 [70 years old. 4 2 (15.38) 1 A similar age-structure pyramid in the CKD population 5 3 (23.08) 2 has been reported from another Asian country, Iran, where Total 13 3 23.6% are aged \30 years, and only 6.0% are [70 years old [4]. In the present cohort, 37% of stage 3–5 CKDu Values are numbers (percentages) of participants unless stated otherwise patients were older than 60 years. CKDu chronic kidney disease of uncertain etiology In our cohort, the probability of death in a 2-year period was 23% for a patient older than 65 years and that was 8% (p = 0.00), and 2.74 (p = 0.09), respectively (Table 4). In for a patient younger than 66 years. These values are multivariate Cox survival analysis, the dominance of almost double those reported by Manns et al. [14], who CKDu stage was observed over other significant factors, showed that the probability of death in a CKD cohort in with an HR of 2.94 (p = 0.001). Alberta, Canada, was 4.81% for patients aged \66 years and 13.29% for those aged [65 years. It is particularly interesting to note that 81% of the Canadian cohort had Discussion CKD stage 1 or 2, 18% had stage 3, and 1% had stage 4 or 5, whereas in our cohort, 50% had stage 1 or 2, 22% had This study is believed to be the first to identify possible risk stage 3, and 28% had stage 4 or 5. This demonstrated that factors of CKDu disease progression and death in a pro- the disease progression in our CKDu cohort was much spective cohort in Madawachchiya, Sri Lanka, where faster than that in western countries, and we suspect that CKDu is endemic. this could be a reason for the higher death rate in our The age-structure pyramid of this CKDu cohort was cohort. The overall death rate in our cohort was 5.3% per broad-based, with a relatively large proportion of younger 100 patient-years, which is higher than the rate reported in patients. For example, 17% of the CKDu patients were Taiwan [15]. Lack of adequate dialysis facilities to manage 123 196 Environ Health Prev Med (2012) 17:191–198 Table 4 Sex-stratified, age-adjusted univariate and multivariate Cox proportional models for CKDu disease progression and death Outcome Type of analysis Variable Hazard 95% Confidence p value ratio interval Disease progression Sex-stratified, age-adjusted univariate analysis Alcohol 3.39 1.43–8.04 0.006 (CKD stage 1–4) Betel 3.61 1.21–10.77 0.021 Hypertension 2.02 0.09–45.34 0.907 NSAID 2.33 0.95–5.71 0.065 Sex-stratified, age-adjusted multivariate Alcohol 3.64 0.87–15.23 0.076 (alcohol, betel, hypertension, NSAID) Betel 1.94 0.52–7.24 0.325 analysis Hypertension 3.38 1.31–8.72 0.011 NSAID 1.28 0.42–3.90 0.662 Death (CKD stage 1–5) Sex-stratified, age-adjusted univariate analysis Hypertension 2.29 0.85–6.17 0.100 CKD stage 3.00 1.71–5.26 0.000 Shrunken kidney 2.74 0.83–9.05 0.097 Sex-stratified, age-adjusted multivariate Hypertension 1.79 0.62–5.17 0.277 (hypertension, CKD stage, shrunken kidney) CKD stage 2.94 1.57–5.51 0.001 analysis Shrunken kidney 0.80 0.21–3.05 0.742 NSAID nonsteroidal anti-inflammatory drug, CKDu chronic kidney disease of uncertain etiology, Betel betel chewing, Alcohol alcohol consumption Table 5 Sex-stratified, age-adjusted univariate and multivariate Cox proportional models of disease progression for stage-specific analysis CKDu Type of analysis Variable Hazard ratio 95% Confidence p value interval Stage 1 Sex-stratified, age-adjusted univariate analysis Hypertension 7.29 1.16–45.81 0.034 Family history 21.63 0.44–1063.31 0.120 Stage 2–3 Sex-stratified, age-adjusted univariate analysis Hypertension 3.07 0.95–9.92 0.060 BMI 0.85 0.72–1.00 0.070 Malaria 0.26 0.08–0.85 0.027 Sex-stratified, age-adjusted multivariate (hypertension, Hypertension 26.14 3.04–224.77 0.003 BMI, malaria) analysis BMI 0.64 0.45–0.91 0.011 Malaria 0.27 0.06–1.22 0.083 BMI body mass index (kg/m ), CKDu chronic kidney disease of uncertain etiology the CKDu patients in this region might have contributed to affected population was male. However, the majority of this higher mortality. published studies have shown female-dominant CKD BMI is associated with CKD [16, 17]. Many researchers cohorts [4, 22, 23]. Further research is needed to determine have reported that higher BMI is a risk factor for CKD in the reasons for male dominance in our study area. How- apparently healthy persons [18, 19]. By contrast, in our ever, factors such as genetic susceptibility and some cohort, only 8% of the patients were overweight behavioral risk factors, such as alcohol consumption and 2 2 (25–29.9 kg/m ) or obese ([30 kg/m ), whereas 42% of betel chewing, which could play a role in increasing dis- the patients were underweight (\18.5 kg/m ). According to ease occurrence, should not be neglected. some studies, malnutrition has been shown to increase Diabetes and hypertension are known risk factors for mortality risk more than high BMI [20, 21], and malnu- CKD [24, 25]. According to the definition of CKDu, trition could have also contributed to the higher death rate patients with diabetes and uncontrollable hypertension in our cohort. were not included in the present cohort. However, it should In our study, men (58%) were at higher risk of CKDu be noted that five patients developed diabetes and several than women were (42%). A similar association has been developed hypertension during the follow-up period. At the reported in a study in Taiwan [15], where 62% of the same time, several patients had mild hypertension at the 123 Environ Health Prev Med (2012) 17:191–198 197 common in the older age groups [30]. In the elderly pop- ulation, eGFR is reduced in the normal aging process, but elderly patients have a greater mortality risk when com- pared with younger patients with the same eGFR range [30]. Therefore, it is likely that elderly patients will die in the middle of the disease process rather than reaching the end stage of CKD. However, our CKDu cohort was rela- tively younger than the cohorts that have been studied in other countries [15, 24, 25]. Thus, we can imagine that these CKDu patients would survive until they reach end- stage CKD, in contrast to the population who are already in the latter part of their life when they begin the disease process. Our study had a number of limitations. The study was started at the initiation of community screening in this endemic area; therefore, we could recruit only a limited number of patients. We used the MDRD formula for esti- Fig. 1 Kaplan–Meier curves showing the probability of chronic kidney disease of uncertain etiology (CKDu) disease progression over mation for GFR, which has not been validated for the Sri the monitoring period with and without self-reported hypertension for Lankan population and across the age range. Therefore, the CKDu stage 1 (glomerular filtration rate [GFR] [90 ml/min/1.73 m ) use of eGFR for staging the patients might not have patients (please refer to the ‘‘Results’’ section in the text for Log-rank reflected the actual GFR for this population. For the test and Wilcoxon test results) exclusion of diabetes mellitus, we used a cut-off HbA1C level of 6.5%. However, previous studies have shown that time of diagnosis of CKDu. Among the factors that were such a cut-off level misses a substantial number of people evaluated as suspected risk factors for disease progression with type 2 diabetes, including some with fasting hyper- in our cohort, hypertension was identified as the leading glycemia, as well as people with impaired glucose toler- determinant of disease progression. Self-reported hyper- ance [31]. Therefore, there is a possibility that we might tension was a significant predictor (p \ 0.05) for disease have recruited some diabetic patients in this cohort because progression, with an HR of 3.38 by multivariate Cox pro- of misdiagnosis. portional model analysis for stage 1–4 patients. Our results suggest a strong correlation between hypertension in the early stage of CKDu and disease progression. Sixty-six Conclusions percent of stage 1 patients in our cohort were from the population aged \30 years, and hypertension showed an In this study, we tried to determine factors possibly asso- HR of 7.26 in a sex-stratified, age-adjusted Cox propor- ciated with progression and mortality of CKDu in a single- tional model for stage 1 patients. A similar correlation was center cohort registered in the Medawachchiya regional observed for stage 2–3 patients, with an HR of 26.16. Many clinic in Sri Lanka. We repeatedly found an association researchers have shown that the prevalence of hypertension between disease progression and hypertension. Men were in South Asian populations is higher than that in western at higher risk of CKDu than women. A significant pro- populations [26]. These results strongly suggest that tight portion of the patients in this cohort were underweight, control of blood pressure, particularly in the early stage of indicating a need for future studies on the nutritional status CKDu, has a beneficial effect to slow down disease of these patients. Compared with findings in western progression. countries and other regions of Asia, younger age at disease CKDu stage was the only factor identified to have a onset, equal patient distribution in different age groups, correlation with death, with HRs of 3.0 and 2.94 by uni- faster disease progression in those with hypertension, variate (sex-stratified and age-adjusted) and multivariate deaths occurring mostly in end-stage CKDu, and relatively Cox proportional model analysis, respectively. This result higher mortality rate are some of the characteristics that is supported by the fact that almost all reported deaths were were identified in this cohort. in patients with stage 4 or 5 disease. In contrast, many Acknowledgments The authors would like to thank Dr. Arjuna studies have reported that CKD patients in western coun- Dandeniya, Dr. Gayan Wijesundara, and Dr. Amila Kodikara; the tries frequently die before developing end-stage CKD [27– temporary lecturers of the Department of Pharmacology, Faculty of 29]. The reason for this could be the difference in age at Medicine, University of Peradeniya, Sri Lanka, for their support in disease initiation, because in many countries, CKD is data handling. This study was supported by the Special Coordination 123 198 Environ Health Prev Med (2012) 17:191–198 Funds for Promoting Science and Technology from the Ministry of 13. United States Renal Data System (USRDS) Annual data report Education, Culture, Sports, Science and Technology in Japan. The 2010. http://www.usrds.org/ funding agency had no role in the study design, data collection, and 14. Manns B, Hemmelgarn B, Tonelli M, Au F, Hiasson C, Dong J, analysis, or in the decision to publish or in the preparation of the Klarenbach C. Population based screening for chronic kidney manuscript. TA, EM, and AK conceived and designed the experi- disease: cost effectiveness study. BMJ. 2010;341:c5869. ments. TA and RC performed the experiments. STMLDS, SN, KHH 15. Chiu Y, Chien K, Lin S, Chen Y, Tsai T, Wu D. Outcomes of and TH statistically analyzed the data. STMLDS, SN, KHH, and AK stage 3–5 chronic kidney disease before end-stage renal disease at wrote the paper. NR, TK, EM, and AK critically revised the draft. All a single center in Taiwan. Nephron Clin Pract. 2008;109: authors read and approved the manuscript. c109–18. 16. Nomura I, Kato J, Kitamura K. Association between body mass Conflict of interest The authors declare that they have no com- index and chronic kidney disease: a population-based, cross- peting interests. sectional study of a Japanese community. Vasc Health Risk Manag. 2009;5:315–20. 17. Chalmers L, Kaskel FJ, Bamgbola O. The role of obesity and its bioclinical correlates in the progression of chronic kidney dis- ease. Adv Chronic Kidney Dis. 2006;13(4):352–64. 18. Hsu CY, McCulloch CE, Iribarren C, Darbinian J, Go AS. Body References mass index and risk for end-stage renal disease. Ann Intern Med. 2006;144:21–8. 19. Gelber RP, Kurth T, Kausz AT, Manson JE, Buring JE, Levey 1. Hwang SJ, Tsai JC, Chen HC. Epidemiology, impact and pre- AS, Gaziano JM. Association between body mass index and CKD ventive care of chronic kidney disease in Taiwan. Nephrology in apparently healthy men. Am J Kidney Dis. 2005;46:871–80. (Carlton). 2010;15(2):3–9. 20. Beddhu S. The body mass index paradox and an obesity, 2. Perlman RL, Finkelstein FO, Liu L, Roys E, Kiser M, Eisele G, inflammation, and atherosclerosis syndrome in chronic kidney Burrows-Hudson S, Messana JM, Levin N, Rajagopalan S, Port disease. Semin Dialysis. 2004;17:229–32. FK, Wolfe RA, Saran R. Quality of life in Chronic Kidney 21. Kalantar-Zadeh K, Block G, Humphreys MH, Kopple JD. Disease (CKD): a cross-sectional analysis in the Renal Research Reverse epidemiology of cardiovascular risk factors in mainte- Institute-CKD study. Am J Kidney Dis. 2005;45(4):658–66. nance dialysis patients. Kidney Int. 2003;63:793–808. 3. Menon V, Sarnak MJ. The epidemiology of chronic kidney dis- 22. Zhang QL, Rothenbacher D. Prevalence of chronic kidney dis- ease stages 1 to 4 and cardiovascular disease: a high-risk com- ease in population-based studies: systematic review. BMC Public bination. Am J Kidney Dis. 2005;45(1):223–32. Health. 2008;8:117. 4. Najafi I, Attari F, Islami F, Shakeri R, Malekzadeh F, Salahi R, 23. Ong-Ajyooth L, Vareesangthip K, Khonputsa P, Aekplakorn W. Gharavi MY, Hosseini M, Broumand B, Haghighi AN, Larijani Prevalence of chronic kidney disease in Thai adults: a national B, Malekzadeh R. Renal function and risk factors of moderate to health survey. BMC Nephrol. 2009;10:35. severe chronic kidney disease in Golestan Province, northeast of 24. Coresh J, Astor BC, Greene T, Eknoyan G, Levey AS. Prevalence Iran. PLoS One. 2010;5(12):e14216. of chronic kidney disease and decreased kidney function in the 5. Brown WW, Peters RM, Ohmit SE, Keane WF, Collins A, Chen adult US population: Third National Health and Nutrition SC, King K, Klag MJ, Molony DA, Flack JM. Early detection of Examination Survey. Am J Kidney Dis. 2003;41:1–12. kidney disease in community settings: the Kidney Early Evalu- 25. Chen J, Wildman RP, Gu D, Kusek JW, Spruill M. Prevalence of ation Program (KEEP). Am J Kidney Dis. 2003;42:22–35. decreased kidney function in Chinese adults aged 35 to 74 years. 6. Ayodele OE, Alebiosu CO. Burden of chronic kidney disease: an Kidney Int. 2005;68:2837–45. international perspective. Adv Chronic Kidney Dis. 2010;17(3): 26. Jones CA, Mawani S, King KM, Allu SO, Smith M, Mohan S, 215–24. Campbell NRC. Tackling health literacy: adaptation of public 7. Chandrajith R, Nanayakkara S, Itai K, Aturaliya TN, Dissanayake hypertension educational materials for an Indo-Asian population CB, Abeysekara T, Harada K, Watanabe T, Koizumi A. Chronic in Canada. BMC Public Health. 2011;11(1):24. kidney disease of uncertain aetiology (CKDue) in Sri Lanka: 27. Adler AI, Stevens RJ, Manley SE, Bilous RW, Cull CA, Holman geographic distribution and environmental implications. Environ RR. Development and progression of nephropathy in type 2 Geochem Health. 2011;409(11):671–5. diabetes: the United Kingdom Prospective Diabetes Study 8. Wanigasuriya KP, Peiris-John RJ, Wickremasinghe R, Hittarage (UKPDS 64). Kidney Int. 2003;63:225–32. A. Chronic renal failure in North Central Province of Sri Lanka: 28. Kovesdy CP, Trivedi BK, Anderson JE. Association of kidney an environmentally induced disease. Trans R Soc Trop Med Hyg. function with mortality in patients with chronic kidney disease 2007;101:1013–7. not yet on dialysis: a historical prospective cohort study. Adv 9. World Health Organization (WHO) country office Sri Lanka- Chronic Kidney Dis. 2006;13:183–8. News letters. http://www.whosrilanka.org/EN/Section1_76.htm 29. Go AS, Chertow GM, Fan D, McCulloch CE, Hsu CY. Chronic Accessed 10 Dec 2010. kidney disease and the risks of death, cardiovascular events, and 10. Levey AS, Bosch JP, Lewis JB, Modification of Diet in Renal hospitalization. N Engl J Med. 2004;351:1296–305. Disease Study Group. A more accurate method to estimate glo- merular filtration rate from serum creatinine: a new prediction 30. O’Hare AM, Choi AI, Bertenthal D, Bacchetti P, Garg AX, Ka- equation. Ann Intern Med. 1999;130:461–70. ufman JS, Walter LC, Mehta KM, Steinman MA, Allon M, McClellan WM, Landefeld CS. Age affects outcomes in chronic 11. The National Kidney Foundation. K/DOQI Clinical practice kidney disease. J Am Soc Nephrol. 2007;18:2758–65. guidelines for chronic kidney disease: evaluation, classification, 31. Herman WH, Fajans SS. Hemoglobin A1c for the diagnosis of and stratification. Am J Kidney Dis. 2002;39:S46–75. diabetes: practical considerations. Pol Arch Med Wewn. 12. Chou CY, Cheng SY, Liu JH, Cheng WC, Kang IM, Tseng YH, Shih 2010;120(1–2):37–40. CM, Chen W. Association between betel-nut chewing and chronic kidney disease in men. Public Health Nutr. 2009;12(5):723–7.

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Environmental Health and Preventive MedicineSpringer Journals

Published: Sep 1, 2011

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