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NDT Advance Access published online on April 9, 2008
Nephrology Dialysis Transplantation, doi:10.1093/ndt/gfn148
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© The Author [2008]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org


Predictors of change in estimated GFR: a population-based 7-year follow-up from the Tromsø study

Jens Kronborg1,5, Marit Solbu1,3, Inger Njølstad2, Ingrid Toft1,3, Bjørn O. Eriksen3,4 and Trond Jenssen1,6

1 Institutes of Clinical 2 Community Medicine, University of Tromsø 3 Department of Nephrology 4 Clinical Research Center, University Hospital of North Norway, Tromsø 5 Department of Internal Medicine, Innlandet Hospital Trust, Lillehammer 6 Department of Nephrology, Rikshospitalet University Hospital, Oslo, Norway

Correspondence and offprint requests to: Jens Kronborg, Department of Internal Medicine, Innlandet Hospital Trust, Olav Aukrustsvej 6 N-2618, Lillehammer, Norway. E-mail: kronborg{at}broadpark.no, kronborg{at}sykehuset-innlandet.no



   Abstract
Top
 Abstract
Introduction
 Methods
 Results
 Discussion
 References
 
Background. Chronic kidney disease is associated with increased cardiovascular mortality, and even mild impairment of renal function is a cardiovascular risk factor. Several studies have investigated the risk factors for the development of end-stage renal disease, but little is known about predictors of change in renal function in the general population.

Methods. The present study included 2249 men and 2192 women without signs of kidney disease at baseline who were followed for 7 years from 1994 to 1995 in the Tromsø Study. Estimated glomerular filtration rate (eGFR) was calculated from the Modification of Diet in Renal Disease study equation. Gender-specific multiple linear regression analyses were used to assess predictors of change in eGFR ({Delta}GFR).

Results. Change in eGFR, measured in ml/min/1.73 m2/year, was associated with systolic blood pressure (SBP) [β-value for a 10-mmHg increase in SBP, men = –0.14, 95% confidence interval (CI) = –0.18 to –0.09; women = –0.07, 95% CI = –0.11 to –0.03] and fibrinogen [β-value for 1 SD increase in fibrinogen, men (1 SD: 0.85 g/L) = –0.12, 95% CI –0.20 to –0.03; women (1 SD: 0.80) = –0.11, 95% CI –0.20 to –0.02]. High alcohol consumption in men and high physical activity in women predicted an increase in eGFR. Higher albumin/creatinine ratio was associated with a decline in eGFR in men only.

Conclusions. Some risk factors for change in GFR seem to be gender specific but both high SBP and high levels of fibrinogen contribute to a more rapid decline in GFR for both men and women.

Keywords: cardiovascular risk factors; gender differences; general population; prospective study; renal function



   Introduction
Top
 Abstract
 Introduction
Methods
 Results
 Discussion
 References
 
Chronic kidney disease (CKD) is associated with increased cardiovascular mortality [1]. Furthermore, several studies have reported high cardiovascular mortality and morbidity even among people with mildly or moderately impaired renal function [1,2]. Thus, even a glomerular filtration rate (GFR) of < 90 ml/min/1.73 m2 is now considered a cardiovascular risk factor [3]. From a public health perspective, the costs and burden of slight decrements in renal function are probably more related to an increased risk of developing cardiovascular disease (CVD) than of developing end-stage renal disease (ESRD) [4]. Moreover, some mechanisms behind renal disease and CVD may be common for the two conditions [5].

Several studies have suggested that renal function declines with age [6–10]. However, most studies have been cross-sectional [10], and risk factors for decline have not been assessed in prospective studies involving populations without signs of kidney diseases. Some community-based studies have assessed the risk of CKD (defined as GFR < 60 ml/min/1.73 m2), but have not been able to include urinary albumin excretion in the analyses [11,12]. Furthermore, it has repeatedly been demonstrated that gender differences exist in the decline of GFR [13–16] and also in the association between risk factors and urinary albumin excretion [17]. A protective role of oestrogen has been proposed [18]. Our goal with the present longitudinal study was to assess risk factors for gender-specific changes in estimated GFR ({Delta}GFR) in a general population.



   Methods
Top
 Abstract
 Introduction
 Methods
Results
 Discussion
 References
 
Subjects
The Tromsø study is a population-based, prospective study involving repeated health surveys of inhabitants of the municipality of Tromsø, Norway. In the fourth survey conducted from 1994 to 1995 (baseline), all inhabitants aged 25 years and older were invited to a brief examination, and 27 158 participated (77% of those eligible). All participants aged 55–74 years and 5–10% sample of the remaining 5-year birth cohorts with > 24 years of age were invited to a second and more comprehensive examination 4–6 weeks later. A total of 9057 persons were invited, and 6819 attended (75% of the eligible population). All participants still residing in Tromsø who attended the baseline study were invited to a follow-up survey in 2001–2002. Between baseline and the follow-up screening, 616 persons had died, 289 had moved and 892 did not want to participate in the follow-up examination, leaving 5022 who attended the follow-up. A total of 4879 of these had measurements of serum creatinine (s-creatinine) at both baseline and follow-up. Subjects who met at least one of the following criteria at baseline were excluded from analyses: GFR > 250 ml/min/1.73 m2 (n = 4), positive urine culture (n = 308), albumin/creatinine ratio (ACR) > 25 mg/mmol for men (n = 26) and ACR > 35 mg/mmol for women (n = 6) or missing values for any of the analysed variables (n = 94). An eGFR > 250 ml/min/1.73 m2 was considered as extreme, and individuals with ACR >25 mg/mmol for men and >35 mg/mmol for women were considered to have CKD.

The final study population included 4441 participants (2249 men and 2192 women).

The persons who did not attend were older [age 62.1 (SD ± 10.5) years versus 59.3 (SD ± 9.8) years, P < 0.0005], were often current smokers (current smokers: 38.1% versus 31.7%, P < 0.0005) and had higher systolic blood pressure (SBP) [143 (SD ± 23) mmHg versus 138 (SD ± 20) mmHg, P < 0.0005] and fibrinogen [3.53 (SD ± 3.5) g/l versus 3.32 (SD ± 3.3) g/l, P < 0.0005] and more often CVD (19.1% versus 11.5%, P < 0.0005) compared with the study population.

Plasma creatinine was analysed by a modified Jaffe reaction; however, because a possible drift in the results between baseline and follow-up was observed, 111 plasma samples from the baseline survey and 142 samples from the follow-up were thawed and reanalysed in 2006 with an enzymatic method (Modular P; Roche Diagnostics, Mannheim, Germany), which is an isotope dilution mass spectrometry (IDMS) traceable method. The plasma samples, which were stored at –70°C, were randomly selected from the range of creatinine between 40 and 180. These creatinine values were fitted to a linear regression model, and adjusted plasma creatinine values were calculated for all participants. Estimated GFR (eGFR) was calculated from the recalibrated four-variable Modification of Diet in Renal Disease (MDRD) study equation [GFR = 175 x (s-creatinine (µmol/l)/88.4) –1.154 x age–0.203 (x0.742 if female)] [19].

Cardiovascular risk factors
At baseline, participants responded to a self-administered questionnaire that included information about smoking habits, alcohol consumption, drug use, physical activity, diabetes mellitus, previous CVD (myocardial infarction, angina pectoris and stroke) and time since last meal. We categorized a time since last meal of more than 5 h as fasting, and all other time intervals as non-fasting. Persons with self-reported diabetes, those who reported using antidiabetic medications and those with serum glucose > 11.1 mmol/L were categorized as having diabetes.

All participants underwent a physical examination involving measurement of height, weight and waist circumference. A trained nurse recorded BP using an automated device (Dinamap Vital Signs Monitor 1846; Critikon, Tampa, FL, USA), with three recordings at 2-min intervals after the participants had been seated for 2 min. The mean of the second and the third measurements was used in this study. A non-fasting blood sample was obtained. Serum total cholesterol was analysed by enzymatic colorimetric methods with commercial kits (CHOD-PAP; Boehringer Mannheim, Mannheim, Germany). Serum HDL cholesterol was measured after the precipitation of lower density lipoprotein with heparin and manganese chloride. Intact proinsulin was measured by a commercial kit (Dako Diagnostics Ltd, Cambridgeshire, UK), using mouse monoclonal antibodies, with no cross-reaction with insulin, C-peptide or 32-33 split proinsulin. Plasma insulin was measured using an ELISA method, a modification of a previously published procedure [20]. The plasma insulin assay had <0.2% cross-reactivity with proinsulin or its primary circulating split form, Des31,31 HPI. Glucose was measured by the hexokinase method photometrically assessing formation of NADPH (Hitachii 917 analyser; Roche Diagnostics). HbA1c levels were measured from the haemolysate by a latex-enhanced turbidimetric immunoassay on a Cobras Mira plus instrument (Unimate 5 HbA1c; Hoffmann-La Roche, Basel, Switzerland).

Three separate morning urine samples were analysed for albumin and creatinine using commercial kits (ABX Diagnostics, Montpellier, France), and the albumin and creatinine values were used to calculate the mean ACR in mg/mmol. One urine sample was cultured. Fibrinogen was measured using the PT-Fibrinogen reagent (Instrumentation Laboratory, Milano, Italy). Insulin/glucose and proinsulin/insulin rates were calculated to reduce the variation inherent in the use of non-fasting insulin and proinsulin values.

Categories of physical activity were divided into active [>1-h hard physical activity a week (with prominent perspiration or breathlessness) and/or >3-h light activity (without prominent perspiration or breathlessness)] or inactive (all others). Physical activity during working hours was not included in the analyses. Hypertension was defined as SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg and/or the use of antihypertensive medication. Participants were classified as current smokers, former smokers or persons who had never smoked. Former smokers who had stopped smoking during the last year before baseline were categorized as current smokers.

Alcohol consumption was divided into four categories: (1) alcohol abstention, those who reported no use of alcohol; (2) low alcohol consumption, ≤ 3 units of alcohol per week; (3) moderate alcohol consumption, >3 and ≤ 6 units of alcohol per week and (4) high alcohol consumption, > 6 units of alcohol per week. One unit of alcohol equals 12 g of alcohol.

Statistical analyses
Baseline data are presented as mean (± SD) or as median (interquartile range) for skewed distributions. Categorical variables are given as proportions. Comparisons by gender were performed with two-tailed t-tests, the Mann–Whitney test or {chi}2 tests as appropriate. Analyses of predictors of the annual {Delta}GFR were done separately for men and women in multiple linear regression analyses using {Delta}GFR in ml/min/1.73 m2/year as dependent variables and baseline variables as independent variables. Change in eGFR was calculated by subtracting eGFR at baseline from eGFR at the follow-up and dividing the difference by the follow-up time in years. A negative {Delta}GFR indicates a fall in eGFR.

Baseline eGFR was included as an independent variable in all regression analyses. Analyses were done with each baseline variable adjusted for age and baseline eGFR as well as with multiple regression models with all the variables entered in a single step. The variables in the multiple regression analyses were chosen in advance to analyse their specific association with changes in GFR when adjusted for known and potential confounders. All continuous variables were tested for non-linear associations by inclusion of the quadratic term in the analyses or by categorizing the variables. The effects of potential interactions were tested for by including the products of the variables in the multiple regression analysis (sex x age, sex x SBP, sex x ACR, sex x physical activity and sex x alcohol consumption) one by one. One sex-specific SD was used as a unit for the continuous variables in the regression analyses. All statistical analyses were performed using SPSS software version 13.0 (SPSS, Inc., Chicago, IL, USA) for Windows. P-values <0.05 were considered statistically significant.



   Results
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 Abstract
 Introduction
 Methods
 Results
Discussion
 References
 
Table 1 gives the characteristics of the participant. Fibrinogen, cholesterol and HDL cholesterol levels were significantly higher in women compared to men. Diastolic BP (DBP) was higher in men, but there was no gender difference in SBP.


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  		Table 1 The Tromsø study: characteristics of the study populationa by sex

 
The unadjusted {Delta}GFR in ml/min/1.73 m2/year was equal between men and women [men: –1.21 (SD 2.11); women: –1.19 (SD 2.23), P = 0.80]. Table 2 shows the age distribution of the population and the unadjusted {Delta}GFR stratified for sex and age.


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  		Table 2 The Tromsø study: {Delta}GFR in ml/min/1.73 m2/year by gender and age

 
Table 3 shows linear regression analyses of associations between {Delta}GFR and baseline characteristics adjusted for age and baseline eGFR. Age, SBP, fibrinogen, ACR and BP treatment were associated with {Delta}GFR in both sexes. High alcohol consumption was associated with an increase in eGFR in men and physical activity was associated with an increase in eGFR in women. Having diabetes or CVD at baseline was linked with decreased eGFR in both genders. In women without diabetes or CVD, HbA1c was related to a decrease in eGFR, but not in men. Because we found no relationships between {Delta}GFR and proinsulin/insulin ratio or insulin/glucose ratio, these variables were not included in the further analyses.


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  		Table 3 The Tromsø study: age- and baseline GFR-adjusted associations between baseline characteristics (1994–1995) and change in GFRa in ml/min/1.73 m2/year by gender

 
In the multiple linear regression analyses, the associations between {Delta}GFR and age, systolic BP, fibrinogen and having diabetes remained significant for both genders, while, CVD and ACR at baseline were no longer linked with {Delta}GFR in women (Table 4). On the other hand, physical activity was still associated with increased eGFR among women, as was high alcohol intake with increased eGFR among men. When alcohol consumption per week replaced categories of alcohol consumption as a continuous variable, alcohol consumption was significant in men (P = 0.036) but not in women (P = 0.911) (data not shown). Current smoking was associated with an increase in eGFR in women. When both men and women were included in the same analysis, the annual decline in eGFR was 0.21 ml/min/1.73 m2/year (95% CI 0.07–0.34) steeper in women compared to men. The quadratic term of age was significant among men (β = –0.07, 95% CI –0.13 to –0.01), but not women. Table 5 shows the β values in the linear regression analysis with age by 10-year categories. In men, the {Delta}GFR was constant until the age of 70, while {Delta}GFR decreased gradually already from the age of 50 years in women compared to those younger than 40 years of age. No other quadratic term was significant. We found no interaction between age and gender.


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  		Table 4 The Tromsø study: multiple linear regression analyses of GFR change* between baseline (1994–1995) and follow-up (2001–2002)

 

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  		Table 5 The Tromsø study. Adjusted* {Delta}GFR in ml/min/1.73 m2/year by gender and age

 
The interaction variable SBP x gender was significant (P = 0.019) in the multiple regression analysis including both genders. When we repeated the multiple regression analysis with SBP in categories, the annual decline in {Delta}GFR became significantly higher in men at SBP > 130 mmHg compared with men with SBP <120 mmHg (Table 6). In women, the annual decline in GFR was constant over lower ranges of SBP and became significantly larger when SBP was > 170 mmHg.


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  		Table 6 The Tromsø study: {Delta}GFR in ml/min/1.73 m2/year by gender and systolic blood pressure

 
Adding the interaction variables of ‘gender x alcohol consumption’ and ‘gender x physical activity’ in a multivariable regression analysis that included both sexes showed that the associations between alcohol consumption, physical activity and {Delta}GFR were gender dependent (P = 0.012 for alcohol consumption and P = 0.010 for physical activity) (data not shown). In multivariate analyses among individuals without diabetes or CVD at baseline (1868 men and 1976 women), we found similar results regarding age, SBP and physical activity (Table 4). However, in this analysis, fibrinogen was no longer associated with {Delta}GFR, and ACR was associated with {Delta}GFR in both sexes. No association was seen between alcohol consumption and {Delta}GFR in men without CVD or diabetes. In men with CVD or diabetes (n = 597), high alcohol consumption was associated with increased eGFR (β = 0.9, 95% CI 0.01 to 1.80). Because erythrocyturia is apparently not associated with renal function decline [8], we did not identify it as an exclusion criterion. A repeated analysis excluding those with erythrocyturia (n = 324) produced essentially unchanged results (data not shown).



   Discussion
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
References
 
The aim of the present study was to evaluate gender-specific risk factors for changes in eGFR in a general population without signs of kidney disease. The reduction in eGFR increased with age, SBP, fibrinogen and in those with diabetes in both sexes. Furthermore, physical activity and current smoking was associated with increased eGFR in women. High alcohol consumption was associated with increased eGFR and ACR and having CVD was associated with decreased eGFR in men. The decline in eGFR was significantly higher in women compared to men when adjusting for risk factors in the multiple regression analysis. In women, the decline in eGFR increased with age while it seemed to be constant until the age of 70 years in men.

Several studies have suggested an annual decline in GFR of 0.6 to 1.1 ml/min/1.73 m2 after age 30–40 years. The majority of these studies were cross-sectional [10,21], using age as a proxy for time. Only a few studies have been longitudinal [6,8,22]. Our estimates for the annual decline in eGFR were 1.21 ml/min/1.73 m2 in men and 1.19 ml/min/1.73 m2 in women in an adult population with a mean age of 59.3 years at baseline. In a cross-sectional study of 365 healthy potential kidney donors (mean age 41.1 years), the mean decline in GFR was 0.49 ml/min/1.73 m2/year [10]. In the Baltimore Longitudinal Study of Aging, the fall in creatinine clearance in 254 ‘normal’ subjects (mean age 56.6 years) was 0.75 ml/min/year [6], and in the PREVEND Study including 8592 persons (mean age 49 years), without macroalbuminuria or erythrocyturia, the annual loss in estimated GFR was 0.55 ml/min/1.73 m2/year [8]. Because the rate of decline in GFR increases with age, much of the difference between our results and earlier studies can be explained by the fact that we studied older persons [18]. More than 50% of the population were 60 years old or older and only 14% were younger than 50 years. Samples were thawed and creatinine reanalysed with an IDMS traceable method to adjust for a possible drift in the creatinine assay. Even so, changes in creatinine concentration during storage cannot be completely excluded and could have introduced systematic error in the GFR estimates. This may have biased our estimates of the mean rates of change in GFR, which should be interpreted with caution. The cross-sectional associations between age and eGFR were 0.59 ml/min/1.73 m2/year at baseline and 0.64 ml/min/1.73 m2/year at the follow-up, i.e. considerably lower than the longitudinal estimates. However, a possible systematic bias of this kind would not be correlated with the independent variables in the regression analyses that would still give unbiased estimates of the effects of the predictors.

We recently reported a negative association between male gender and the decline of eGFR in people with established kidney disease [13]. This finding agrees with other studies addressing gender-specific changes in kidney function among persons with established kidney disease [14], but not all [15]. In accordance with our findings, Jafar et al. found no sex difference in unadjusted analyses but an adjusted RR of 1.36 (95% CI 1.06–1.75) for doubling of baseline creatinine in women compared to men [15]. They suggest that the discrepancy with earlier studies may reflect lack of adjustment for confounding factors at baseline.

Only a few studies have assessed the gender differences in renal function decline in people without a renal disease. In a cross-sectional study including 122 potential kidney donors (age 21–67 years), a significant decline in GFR with age was found only in men [16]. The age distribution in that study was, however, somewhat younger than in our study, and the preservation of the GFR among women could represent oestrogenic pre-menopausal protection. Indeed, a pre-menopausal preservation of GFR seems to be present in both animal and human models. A direct protective effect of oestrogens (potent antigrowth effect on glomerular mesangial cells), a potential deleterious effect of androgens on renal haemodialysis and a more preserved nitrogen oxide production in females have all been suggested as causes for this gender difference [18]. In our study however, most of the women were post-menopausal.

Elevated BP is a strong and independent risk factor for the development of ESRD [23]. We found a more pronounced fall in eGFR at a moderately elevated SBP in men (140 mmHg), but the annual change in eGFR remained constant in women with increasing SBP until > 170 mmHg. Similar, but weaker, associations were found with substitution of SBP with other BP measures (DBP, mean BP and pulse pressure) (data not shown). The gender difference in the effect of SBP was significant.

The impact of moderately elevated BP on kidney function in apparently healthy individuals has not been extensively addressed in prospective studies. Stewart et al. [24] recently showed that community hypertension levels were not correlated with incidence of hypertensive end-stage kidney disease. Our results are more in accordance with the results of a non-concurrent prospective study among 1399 individuals, which showed that a small increase in BP was associated with hypercreatinaemia [25]. Furthermore, the Kaiser Permanente of North California study, a historical cohort study of more than 300 000 participants, showed that a modest elevation in BP is an independent risk factor for ESRD [26].

People with CKD exhibit evidence of low-grade inflammation with increased fibrinogen and C-reactive protein (CRP) levels [27]. A prospective, population-based study among elderly individuals identified a significant association between increases in creatinine and various inflammatory markers such as fibrinogen and CRP [28]. In the Italian Longitudinal Study of Ageing, fibrinogen independently predicted a rise in creatinine in individuals without current kidney disease [7]. We found similar associations for both sexes in our study. In the population without diabetes and CVD, however, the association was not significant in women.

The association between albumin excretion and GFR in a population without kidney disease has not been clearly determined, and increased albuminuria has been associated with both elevated and reduced creatinine clearance in cross-sectional studies [29,30]. In the present study, higher ACR was associated with a fall in eGFR in men when those with diabetes and CVD were included and in both sexes without diabetes and CVD.

There is growing evidence that smoking is an important risk factor for progression of established nephropathy [31]. The relationship between renal function and smoking is, on the other hand, more uncertain in the general population [30,32–34], and smoking has been associated with both decreased and elevated GFR in a general population [32]. A large population-based, case-control study identified an increased risk of chronic renal failure only in heavy smokers [35]. In the current study, we found an association between increased eGFR and current smoking when compared to nonsmokers in women but not in men. A possible explanation for this finding could be the negative effect of smoking on skeletal muscle mass and thus on creatinine production [36]. Smoking has also been associated with glomerular hyperfiltration [32,33], but we would assume that a time span of 7 years with hyperfiltration would result in a reduced GFR.

High alcohol consumption was associated with higher eGFR in men but not in women, a relationship mainly present among participants with CVD and/or diabetes. Results from earlier studies addressing alcohol consumption and kidney function have been ambiguous. In retrospective case-control studies, lower s-creatinine [37] and an increased risk of ESRD [38] have been linked to higher alcohol intake. One prospective study of women found no association between alcohol consumption and the development of renal dysfunction [39], and in accordance with our results, the prospective Physicians Health Study identified an inverse relationship between moderate alcohol consumption (seven drinks or more weekly) and the risk of renal dysfunction in men [40].

A shortcoming of the present study is that we used the abbreviated MDRD equation to estimate GFR. Use of this equation in the general population has been criticized [10,41]. The low precision of eGFR among individuals with normal renal function may have resulted in the underestimation of effects and increased the probability of type II statistical errors. On the other hand, measuring GFR with iohexol or radioactive markers is costly and unfeasible in larger, population-based studies. Most studies assessing the applicability of the MDRD equation have been cross-sectional, comparing estimated and measured GFR values [10,41], and several of them did not solve the problems with calibration of s-creatinine sufficiently [42]. However, Hallan et al. found almost unbiased estimates for GFR in persons with renal function at normal levels and in all age groups (+0.5 to –2.0 ml/min/1.73 m2), using IDMS traceable creatinine and the re-expressed MDRD formula [42]. Furthermore, a possible systematic bias when using eGFR is most important in the analysis of absolute eGFR values, but of less importance for assessing change in eGFR, which was the focus of the present study. When plasma creatinine replaced eGFR in our models, we observed essentially the same associations between risk factors and the increase in s-creatinine over time (data not shown). Until new methods for measuring renal function that are both precise and accurate and still practically feasible are found, assessments of change in renal function in epidemiologic studies must be made with creatinine or estimates based on creatinine.

Strengths of this study include the large sample size, the high participation rate and the prospective design. Moreover, we excluded individuals with kidney disease (proteinuria), included urinary albumin excretion in the analyses and controlled for diabetes and CVD. Non-participants in the follow-up survey were older, smoked more and had higher SBP and fibrinogen and more CVD compared with those who participated. This bias towards healthier participants may have weakened the true relationship between risk factors at baseline and {Delta}GFR.

In conclusion, we found that increased SBP and fibrinogen were associated with a more rapid decline in eGFR in both sexes. In men, the association between SBP and {Delta}GFR occurred at lower SBP (≥130 mmHg) compared to women (170 mmHg). ACR was associated with a fall in eGFR in men only. In general, the risk factors for decreased eGFR in this low-risk population did not differ from those seen with more advanced renal failure or with CVD.



   Acknowledgments
 
The present study was supported financially by The Norwegian Research Council, The Norwegian Foundation for Health and Rehabilitation, Innlandet Hospital Trust and University Hospital of North Norway Trust. We appreciate the superb technical assistance of Åse L. Bendikssen, Jorunn H. Eikrem and Hege Appelbom at the Laboratory of Metabolic Research, University of Tromsø.

Conflict of interest statement. None declared.



   References
Top
 Abstract
 Introduction
 Methods
 Results
 Discussion
 References
 

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Received for publication: 9.10.07
Accepted in revised form: 25. 2.08


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