1 Menzies School of Health Research and 2 Flinders University NT Clinical School, Darwin, 3 University of Sydney, Sydney and 4 Centre for Chronic Disease, University of Queensland, Brisbane, Australia
Correspondence and offprint requests to: Dr Stephen McDonald, ANZDATA Registry, The Queen Elizabeth Hospital, 28 Woodville Rd, Woodville, SA 5011, Australia. Email: stephenm{at}anzdata.org.au
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Abstract |
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Methods. A cross-sectional community survey was conducted. Markers of early renal disease examined included urine albumin/creatinine ratio (ACR), serum creatinine concentration and calculated glomerular filtration rate (GFR). CV risk markers included blood pressure as well as measures of glycaemia, diabetes and serum lipids.
Results. The study group included 237 people, 58% of the adult population of the community. The crude prevalence of microalbuminuria (urine ACR: 3.433.9 g/mol, 30299 mg/g) was 31% and of overt albuminuria (urine ACR: 34 g/mol,
300 mg/g), 13%. The prevalence of overt albuminuria increased with age, but the prevalence of microalbuminuria was greatest in the 4554 year age group. Microalbuminuria was associated with increasing body mass index, whereas overt albuminuria was associated with increasing glycated haemoglobin (HbA1c) and systolic blood pressure and a history of diabetes. The prevalence of elevated serum creatinine concentration (
120 µmol/l) was 10%. GFR (calculated using the MDRD equation) was <60 ml/min/1.73 m2 in 12% and 6079 ml/min/1.73 m2 in a further 36% of the study population. Although many people with albuminuria had well preserved GFRs, mean GFR was lower in people with higher levels of albuminuria.
Conclusions. The high prevalence of markers of renal disease in this community was consistent with their high rates of ESRD. The distribution of microalbuminuria suggested a cohort effect, representing a group who will progress to overt albuminuria. The powerful association of renal disease markers with CV risk factors confirms a strong link between renal and CV disease in the early, asymptomatic stages of each. Thus, pathologic albuminuria, in part, might be a manifestation of the metabolic/haemodynamic syndrome and both conditions might arise out of a common menu of risk factors. Hence, a single agenda of primary and secondary intervention may benefit both.
Keywords: albuminuria; Australian Aborigines; cardiovascular disease; cardiovascular markers; end-stage renal disease
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Introduction |
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On a national level, a high incidence of treated ESRD among AA groups has been demonstrated from registry data. Rates differ between regions and communities, with a 10-fold or greater variation in ESRD incidence [10]. High but variable prevalence rates of albuminuria demonstrated in several Aboriginal communities are compatible with this excess of ESRD [1113]. Rates of cardiovascular disease and cardiovascular death are also considerably higher among AA people. Observed cardiovascular death rates range from two to five times the national average [14] and are increased by >10-fold in young adults.
The AA community in which the association between early renal disease and cardiovascular mortality was studied previously had an ESRD incidence rate of 2700 per million and a 34-fold increase in cardiovascular deaths. There, albuminuria was shown to be inversely correlated with CockcroftGault estimated creatinine clearance and directly correlated with body mass index (BMI), blood pressure, insulin and lipids on cross-sectional survey [11]. Albuminuria predicted not only all cases of ESRD [15], but also most cases of cardiovascular death on longitudinal study [9]. These findings suggested that, in that community, renal and cardiovascular diseases were intimately related, even in their early and asymptomatic stages.
Challenges exist, however, when assessing early renal disease among AA communities. The validity of formulae used to calculate creatinine clearance or GFR have not been tested in this racial group. Differences in body composition between Aboriginal and non-Aboriginal Australians have been identified [16], which might affect the validity of such estimates. Popular formulae used to predict GFR, such as the MDRD formula [17] and that of Cockcroft and Gault, are empirically derived; hence, one cannot readily control for potentially differing body composition between different racial groups, although the MDRD equation includes a correction factor for African Americans. Neither formula has been validated among Aboriginal Australians, in whom there may be a lower proportion of lean muscle mass for a given BMI [16].
To further explore the relationship between markers of renal disease and cardiovascular risk, we performed a cross-sectional survey in another remote Aboriginal community. This community was located in a remote coastal area of the Northern Territory (NT) of Australia, 600 km from Darwin (and a similar distance from the community previously reported [11,15]). This community was typical of remote Aboriginal communities, with high rates of poverty, household crowding and unemployment. In the 1996 Australian Census, in this community 82% of adult residents reported a weekly income <$A 200, only 6% were part of the labour force and an average of 7.8 people per occupied dwelling. Over the 10 year period 19912001, crude ESRD incidence rate in this community was 590 per million per year, in contrast to the Australia average of 7090 per million per year over this time. Age at commencement of renal replacement therapy was also younger; the indirectly age-standardized ESRD rate was 15 times the non-indigenous rate. Cardiovascular mortality was also elevated, with an age-adjusted regional rate of 700 per million per year for AA males and 540 per million per year for females for the period 198695, compared with the NT non-Aboriginal rates of 300 and 170 per million per year for males and females, respectively [14].
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Subjects and methods |
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Blood and urine specimens were non-fasting and collected without regard for time of day. Serum was separated immediately after clotting, within 20 min in all cases. All specimens were then refrigerated until transfer to the pathology laboratory by air, within 24 h.
Serum was analysed for electrolytes, urea, creatinine, liver function tests, total and high-density lipoprotein (HDL) cholesterol, Lp(a) and triglycerides using a standard automated analyser (Hitachi 917 Autoanalyser, Boehringer-Mannheim, Rotkreuz, Germany).
The proportion of glycated haemoglobin (HbA1c) was used as the measure of glycaemia for all participants and was analysed on whole venous blood. Low-density lipoprotein (LDL) cholesterol concentrations were calculated using the Friedewald equation if serum triglyceride concentration was <4.5 mmol/l. Given the non-fasting nature of the serum specimens, triglyceride concentrations were not further analysed. Albumin and creatinine concentrations were analysed in the spot urine sample and an albumin/creatinine ratio (ACR) calculated. This was classified into normal (ACR: <3.4 g/mol, <30 mg/g), microalbuminuria (ACR: 3.433.9 g/mol, 30299 mg/g) and overt albuminuria (ACR: 34 g/mol,
300 mg/g) [18].
Analyses were carried out using standard statistical software (Intercooled Stata version 7.0, Stata Corporation, College Station, TX, USA). Serum creatinine was analysed using an inverse transformation and urine albumin and creatinine concentration were log-transformed. Where urine ACR was analysed as a continuous variable, a shifted log transformation [ln(ACR-0.217) g/mol] was used to correct the right skew. Means and confidence intervals (CIs) for all transformed variables are presented after back-transformation to their original scale. For multivariate analyses, ACR was analysed as categories of normal, microalbuminuria and overt albuminuria. Multinomial logistic regression was used to analyse the relationship of the albuminuria categories. This allowed derivation of separate odds ratios (ORs) for micro- and overt albuminuria, compared with the normal ACR group. Goodness of fit of continuous predictor variables in logistic models was examined with the HosmerLemeshow test; predictors were analysed as categories where this test suggested a poor fit as a continuous variable.
GFR was estimated from serum creatinine, urea and albumin concentrations using the MDRD Equation 7 [17]. A second estimate was made using the CockcroftGault equation. This was corrected for body surface area (BSA) to allow comparison with the MDRD calculation. Other formulae were not examined here as the CockcroftGault and MDRD formulae are those commonly in clinical use. Agreement between the MDRD and CockcroftGault estimates was then examined using the limits of agreement method of Bland and Altman.
The study protocol was approved by the Joint Institutional Ethics Committee of Menzies School of Health Research and Royal Darwin Hospital.
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Results |
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Harmonic mean serum creatinine concentration was significantly higher among males (Table 1). There was a significant negative correlation between age and serum creatinine (r = 0.31, P < 0.001). Height (r = 0.44, P < 0.001) and weight (r = 0.18, P = 0.007) were also correlated with serum creatinine. The MDRD GFR and the creatinine clearance from the CockcroftGault calculations were significantly correlated (Pearson r = 0.8, P < 0.001). The values from each equation were similar on average [mean difference 0.62 (1.10, 2.34) ml/min/1.73 m2]. Although the MDRD GFR did not differ with gender, the mean CockcroftGault GFR was lower among males (Table 1). The BlandAltman limits of agreement were broad (24.6 to 25.9 ml/min/1.73 m2) and were similar in males and females. This suggests substantial variation when the results from each formula are compared in an individual. The MDRD formula was used for subsequent comparisons, except where otherwise stated.
There was no significant difference in calculated GFR with gender, but there was significant variation with age, with a steadily decreasing GFR with age (Figure 3). After adjustment for age, calculated GFR was significantly lower in those with diabetes [in whom the mean GFR was 6.4 (2.010.9) ml/min/1.73 m2 lower; P = 0.005] and inversely with SBP [GFR decreased 1.2 (0.12.2) ml/min/1.73 m2 per 10 mmHg increase in SBP; P = 0.03]. Calculated GFR was not associated with smoking or BMI, but did vary significantly across the quartiles of HbA1c (ANOVA; P < 0.0001). When adjusted for age and gender, however, the variation of GFR with HbA1c quartile was not significant (P = 0.5). Calculated GFR fell with increasing serum cholesterol concentration and decreasing serum HDL cholesterol concentration, but was not significantly associated with calculated LDL cholesterol concentration. After adjustment for age and gender, calculated GFR remained significantly associated with HDL cholesterol concentration [mean GFR increased 4.2 (0.08.5) ml/min/1.73 m2 per doubling of HDL cholesterol concentration; P = 0.05].
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Discussion |
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These observations confirm and extend the associations of albuminuria with renal function and cardiovascular risk reported in one other AA community [11] and support the predictive value of albuminuria for CV death [9]. It appears likely, therefore, that these associations can be generalized to other AA communities with a high prevalence of renal disease and possibly to other indigenous groups. The degree of albuminuria and reduced GFR represent a large asymptomatic base to a pyramid of renal disease, the tip of which is manifest as ESRD. Among the large proportion of the population with asymptomatic renal disease, there were strong correlations between renal and most cardiovascular risk factors. Only one urine ACR estimation was obtained in this study. Since there is substantial biological variability in albumin excretion [19], this will have led to non-differential misclassification of albuminuria category. This will, however, obscure associations rather than lead to bias.
The prevalence of albuminuria was strongly age-related, although the patterns for micro- and overt albuminuria differed. This probably represents a combination of cohort effects. Firstly, older people have experienced more nephropathic risk factors than younger people (e.g. low birth weight, infections) and, secondly, the progression of albuminuria in individuals over time, as has been shown in another Aboriginal community [15]. The lower GFRs in people with micro- and overt albuminuria are consistent with a role of albuminuria as a predictor of declining renal function. However, the high prevalence of micro- and overt albuminuria in the group with normal creatinine and GFR emphasizes the utility of ACR as a marker of risk of renal disease when renal excretory function is still well preserved.
The GFR values calculated from the CockcroftGault and MDRD equations were significantly correlated. There was, however, poor agreement between the two methods in individuals when quantitated in the BlandAltman approach. Although there was not a trend of either method to systematically under- or over-estimate GFR compared with the other, the weighting of gender led to difference comparisons between formulae. GFR estimates from both formulae had similar relationships to ACR and to cardiovascular risk factors. However, the applicability of these formulae to Aboriginal people still needs to be evaluated. The lower muscle mass for a given BMI in Aboriginal Australians [16], however, suggests that creatinine-based formulae of any sort may underestimate the degree of renal insufficiency in these groups.
The distribution of renal markers can now be compared with studies based in non-indigenous populations. The recent Australian study AusDiab measured spot urine ACR on a stratified sample representative of the non-indigenous Australian population. The prevalence of pathological albuminuria, using the same definitions as this study, was much lower with microalbuminuria detected in 6.1% and overt albuminuria in 0.7% [20]. This study also reported a median GFR (from the CockcroftGault formula standardized to BSA) of 89 ml/min/1.73 m2, similar to the mean value observed here. In the AusDiab study, however, a CockcroftGault GFR value <60 ml/min/1.73 m2 was seen in 3.4% in contrast to the present study where 16% had a CockcroftGault GFR value in this range. This is primarily attributable to differences in creatinine: the AusDiab prevalence of serum creatinine >120 µmol/l was 1.1% [21]; in contrast, 10% of the cohort studied here had a serum creatinine 120 µmol/l. Thus, the prevalence rates of both albuminuria and higher creatinine are increased compared with available Australian non-Aboriginal data. This suggests that the high rates of ESRD observed among this AA group arise from a widespread prevalence of milder degrees of renal impairment.
The rates of diabetes, smoking, hypertension and overweight described here are similar to those in the previous AA community studied with high ESRD rates [11]. The HbA1c levels were consistent with the high prevalence of diabetes. Rates of diabetes and smoking were considerably higher than those in the contemporary non-Aboriginal Australian population; although rates of overweight and hypertension were lower [21]. The associations of BMI, diabetes, HbA1c and blood pressure with albuminuria and of diabetes, blood pressure and lower HDL cholesterol with lower GFRs, underscore the associations between renal disease and cardiovascular risk. There is a quantitative dimension to the association between renal and cardiovascular risk also; diabetes and higher SBP, representing later stages of metabolic and vascular disease, were associated with overt albuminuria, whereas increasing BMI can be seen as an earlier marker of metabolic changes and was associated with an earlier stage of renal disease. This is compatible with the predictive value of albuminuria for cardiovascular death demonstrated in another remote Aboriginal community [9,15], in non-indigenous communities elsewhere [22] and the high prevalence of diabetes and cardiovascular disease in both the indigenous and non-indigenous ESRD populations.
The lack of a positive relationship between smoking and renal disease is contrary to reports on smoking and renal disease in other populations, but compatible with findings in the other community studied [11]. Perhaps, in a cash-poor environment, cigarette smoking marks relative affluence in these populations, which itself partially protects against renal and other diseases.
The links between the indices of impaired renal function and diabetes and hypertension shown here emphasize that in this environment, chronic non-communicable lifestyle diseases do not occur in isolation, but cluster together with the attendant increased mortality risks. The widely reported association of cardiovascular disease with renal impairment reflects an intimate relationship in early and asymptomatic disease, related to a common menu of risk factors. Whether there is also a specific atherosclerotic effect of mild renal impairment (perhaps by alterations in LDL oxidation [23,24] or other means) in addition to the associated risk factors is not clear. The close associations with cardiovascular risk factors have important implications for screening and treatment programs, which need to address multiple health issues simultaneously.
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References |
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