Gender differences in predictors of the decline of renal function in the general population
2008; Elsevier BV; Volume: 74; Issue: 4 Linguagem: Inglês
10.1038/ki.2008.200
ISSN1523-1755
AutoresNynke Halbesma, Auke H. Brantsma, Stephan J. L. Bakker, Désirée F. Jansen, Ronald P. Stolk, Dick de Zeeuw, Paul E. de Jong, Ronald T. Gansevoort, for the PREVEND study group,
Tópico(s)Blood Pressure and Hypertension Studies
ResumoWe sought to identify predictors of the decline in renal function, especially those that are modifiable, in the 5488 participants of the prospective, community-based cohort study PREVEND who completed three visits during a mean follow-up of 6.5 years. The change in renal function was used as the outcome and this was calculated as the linear regression of three estimated GFR measurements obtained during follow-up. Risk factors, known to influence renal outcome in patients with primary renal diseases, were used as potential predictors in multivariate regression analyses. High systolic blood pressure and plasma glucose were found to be independent predictors for an accelerated decline in function for both genders. In males, albuminuria was the strongest independent predictor for renal function decline, whereas in females albuminuria was univariately associated only after adjustment for age. The direction of the association between cholesterol/HDL ratio and decline of renal function differed by gender. Surprisingly, in males, waist circumference was an independent predictor and positively associated with renal function outcome. These studies show that there are gender differences in the standard predictors of the decline in renal function. We sought to identify predictors of the decline in renal function, especially those that are modifiable, in the 5488 participants of the prospective, community-based cohort study PREVEND who completed three visits during a mean follow-up of 6.5 years. The change in renal function was used as the outcome and this was calculated as the linear regression of three estimated GFR measurements obtained during follow-up. Risk factors, known to influence renal outcome in patients with primary renal diseases, were used as potential predictors in multivariate regression analyses. High systolic blood pressure and plasma glucose were found to be independent predictors for an accelerated decline in function for both genders. In males, albuminuria was the strongest independent predictor for renal function decline, whereas in females albuminuria was univariately associated only after adjustment for age. The direction of the association between cholesterol/HDL ratio and decline of renal function differed by gender. Surprisingly, in males, waist circumference was an independent predictor and positively associated with renal function outcome. These studies show that there are gender differences in the standard predictors of the decline in renal function. Chronic kidney disease (CKD) is a growing public health problem worldwide.1.Gilbertson D.T. Liu J. Xue J.L. et al.Projecting the number of patients with end-stage renal disease in the United States to the year 2015.J Am Soc Nephrol. 2005; 16: 3736-3741Crossref PubMed Scopus (296) Google Scholar In 2000, approximately 300,000 patients had end-stage renal disease (ESRD) in the United States alone, and this number is expected to double by the year 2010.2.Xue J.L. Ma J.Z. Louis T.A. et al.Forecast of the number of patients with end-stage renal disease in the United States to the year 2010.J Am Soc Nephrol. 2001; 12: 2753-2758PubMed Google Scholar Furthermore, the earlier stages of CKD are expected to be about 80 times more prevalent.3.National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification.Am J Kidney Dis. 2002; 39: S1-S266Abstract Full Text Full Text PDF PubMed Scopus (228) Google Scholar Given these expectations, it is evidently important to identify risk factors of renal function decline. Such factors can be implemented in screening programs to identify subjects at high risk of renal function decline, who may benefit from early preventive treatment. Most studies that have been performed on this topic have reported on predictors of the development of CKD (estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m2) or ESRD. However, the adverse consequences of renal insufficiency appear not to be limited to those whose renal function falls below a certain threshold. For instance, even subjects with relatively minor impairment of renal function are already at increased risk of cardiovascular disease.4.Henry R.M. Kostense P.J. Bos G. et al.Mild renal insufficiency is associated with increased cardiovascular mortality: the Hoorn Study.Kidney Int. 2002; 62: 1402-1407Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar,5.Fried L.F. Shlipak M.G. Crump C. et al.Renal insufficiency as a predictor of cardiovascular outcomes and mortality in elderly individuals.J Am Coll Cardiol. 2003; 41: 1364-1372Abstract Full Text Full Text PDF PubMed Scopus (415) Google Scholar,6.Menon V. Sarnak M.J. The epidemiology of chronic kidney disease stages 1 to 4 and cardiovascular disease: a high-risk combination.Am J Kidney Dis. 2005; 45: 223-232Abstract Full Text Full Text PDF PubMed Scopus (49) Google Scholar,7.Zhang L. Zuo L. Wang F. et al.Cardiovascular disease in early stages of chronic kidney disease in a Chinese population.J Am Soc Nephrol. 2006; 17: 2617-2621Crossref PubMed Scopus (37) Google Scholar,8.Foley R.N. Murray A.M. Li S. et al.Chronic kidney disease and the risk for cardiovascular disease, renal replacement, and death in the United States Medicare population, 1998 to 1999.J Am Soc Nephrol. 2005; 16: 489-495Crossref PubMed Scopus (746) Google Scholar The Hoorn study, a prospective population-based study including subjects with an eGFR ranging from 17 to 117 ml/min/1.73 m2 reported that a 5 ml/min/1.73 m2 lower eGFR was associated with a 26% increase in the risk of cardiovascular death over the entire range of baseline renal function.4.Henry R.M. Kostense P.J. Bos G. et al.Mild renal insufficiency is associated with increased cardiovascular mortality: the Hoorn Study.Kidney Int. 2002; 62: 1402-1407Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar Therefore, we aimed to investigate predictors of renal function decline, especially modifiable ones, in subjects over a broad eGFR range. For this analysis, we used data of subjects who participated in a community-based prospective cohort study. As outcome variable we calculated for each participant the slope through three eGFR values over time. Multivariate regression analysis was applied to identify variables that were associated with renal function decline. Mean follow-up of the 5488 subjects in this analysis was 6.5 years (35,500 person-years of follow-up). Baseline characteristics of the overall study population are given in Table 1. Of note, the results of multivariate linear regression analyses showed that gender was a strong effect modifier, because a significant interaction term was found between urinary albumin excretion (UAE) and gender (P<0.001), and between cholesterol/high-density lipoprotein (HDL) ratio and gender (P=0.005) versus the change in eGFR over time. The statistical significance of these interaction terms indicate that the association between UAE versus outcome and cholesterol/HDL ratio versus outcome is not similar in males and females. Therefore, we stratified all further analyses by gender. Consequently, Table 1 shows also baseline characteristics for males (n=2770) and females (n=2718) separately. At baseline, males had a significantly higher waist circumference, systolic blood pressure, percentage ACEi/A2A treatment, cholesterol/HDL ratio, percentage lipid lowering treatment, triglycerides, plasma glucose, and a higher UAE, urea, and sodium excretion and also a higher eGFR. For males, the range of UAE is 1.18–2960 mg/24 h and for females it is 1.0–3610 mg/24 h. For males, the eGFR values are between 23.2 and 155.9 ml/min/1.73 m2 and for females the values are between 21.9 and 136.3 ml/min/1.73 m2. The mean eGFR slope over time in males was -0.55±1.47 ml/min/1.73 m2/year, and in females it was -0.33±1.41 ml/min/1.73 m2/year (P<0.001 for males versus females). The mean serum creatinine levels during the three screening rounds were 83.6±14.4, 84.9±19.0, and 85.1±22.9 μmol/l, respectively.Table 1Baseline characteristics for the overall study population and for males and females separatelyOverall (N=5488)Males (N=2770)Females (N=2718)P-valueAge (years)49 (12)50 (12)48 (11)<0.001Smoking (%)34.534.334.7NSPositive family history (%)31.331.131.40.003Waist circumference (cm)88.1 (12.7)93.3 (10.8)82.8 (12.3)<0.001SBP (mm Hg)128 (19)133 (18)123 (19)<0.001 Antihypertensive medication (%)14.515.513.50.012 ACEi/A2A medication (%)4.25.13.2<0.001Cholesterol/HDL ratio4.6 (1.8)5.2 (1.9)4.0 (0.5)<0.001Triglycerides (mmol/l)†1.1 (0.8–1.7)1.3 (0.9–1.9)1.0 (0.8–1.5)<0.001 Lipid lowering medication (%)6.27.05.4<0.001Glucose (mmol/l)4.9 (1.2)5.0 (1.3)4.7 (1.0)<0.001 Antidiabetic medication (%)1.31.41.2NSCRP (mg/l)†1.20 (0.53–2.74)1.16 (0.52–2.49)1.24 (0.53–3.03)0.001UAE (mg/24 h)†9.0 (6.2–15.3)10.0 (6.8–18.8)8.1 (5.8–12.9)<0.001Urinary urea excretion (mmol/24 h)361 (103)397 (105)324 (88)<0.001Urinary sodium excretion (mmol/24 h)143 (50)159 (52)127 (42)<0.001eGFR (ml/min/1.73 m2)80.7 (13.9)83.8 (14.3)77.5 (12.7)<0.001ACEi, angiotensin converting enzyme inhibitors; A2A, angiotensin-II antagonists; CRP, hs C-reactive protein; eGFR, estimated glomerular filtration rate (MDRD); HDL, high-density lipoprotein; SBP, systolic blood pressure; NS, not significant; UAE, urinary albumin excretion.Values are given as mean (s.d.), or median (interquartile range) in case of skewed data (†) distribution. Statistical analyses, to test the differences between males and females, were performed with t-test, Mann–Whitney test in case of skewed distribution, or χ2 test in case of categorical variables. Open table in a new tab ACEi, angiotensin converting enzyme inhibitors; A2A, angiotensin-II antagonists; CRP, hs C-reactive protein; eGFR, estimated glomerular filtration rate (MDRD); HDL, high-density lipoprotein; SBP, systolic blood pressure; NS, not significant; UAE, urinary albumin excretion. Values are given as mean (s.d.), or median (interquartile range) in case of skewed data (†) distribution. Statistical analyses, to test the differences between males and females, were performed with t-test, Mann–Whitney test in case of skewed distribution, or χ2 test in case of categorical variables. Table 2 shows the results of the univariate linear regression analyses, and Table 3 shows the effect of correction for age and baseline eGFR. In both males and females, systolic blood pressure, plasma glucose, and UAE were significantly and negatively associated with slope of renal function, indicating that a higher systolic blood pressure, plasma glucose and UAE were associated with a larger decline in eGFR. Other variables were only associated with renal function decline in one of the genders. For instance, Ln CRP was only associated with renal function decline in females. Surprisingly, some variables were associated differently in the two genders: in males, lower waist circumference and a lower cholesterol/HDL ratio predicted accelerated renal function decline, whereas in females an opposite association was found.Table 2Univariate associations between baseline characteristics and change in renal function during follow-up (assessed as slope through three eGFR values over time per individual)Males (N=2770)Females (N=2718)Standardized betaP-valueStandardized betaP-valueSmoking0.005NS−0.003NSPositive family history−0.003NS−0.010NSWaist circumference0.0520.006−0.023NSSBP−0.074<0.001−0.0460.016Cholesterol/HDL ratio0.069<0.001−0.0490.011Ln_Triglycerides0.0540.0050.015NSGlucose−0.135<0.001−0.104<0.001Ln_CRP−0.026NS−0.028NSLn_UAE−0.126<0.001−0.0380.045Urinary urea excretion0.025NS−0.025NSUrinary sodium excretion0.021NS−0.027NSCRP, hs C-reactive protein; eGFR, estimated glomerular filtration rate (MDRD); HDL, high density lipoprotein; NS, not significant; SBP, systolic blood pressure; UAE, urinary albumin excretion.In case of skewed distribution, data were Ln-transformed to obtain normal data distribution. A negative standardized beta indicates that the higher the value of the variable under study, the more negative the slope of renal function over time is. Open table in a new tab Table 3Associations between baseline characteristics and change in renal function during follow-up (assessed as slope through three eGFR values over time per individual), with correction for baseline eGFR and age.Male (N=2770)Female (N=2718)Standardized betaP-valueStandardized betaP-valueSmoking0.027NS0.018NSPositive family history−0.005NS0.002NSWaist circumference0.0480.014−0.0390.046SBP−0.092<0.001−0.074<0.001Cholesterol/HDL ratio0.0520.005−0.0560.004Ln_Triglycerides0.029NS−0.010NSGlucose−0.126<0.001−0.094<0.001Ln_CRP−0.017NS−0.0380.041Ln_UAE−0.145<0.001−0.0460.012Urinary urea excretion0.020NS−0.026NSUrinary sodium excretion0.022NS−0.022NSCRP, hs C-reactive protein; eGFR, estimated glomerular filtration rate (MDRD); HDL, high density lipoprotein; NS, not significant; SBP, systolic blood pressure; UAE, urinary albumin excretion.In case of skewed distribution, data were Ln-transformed to obtain normal data distribution. A negative standardized beta indicates that the higher the value of the variable under study, the more negative the slope of renal function over time. Open table in a new tab CRP, hs C-reactive protein; eGFR, estimated glomerular filtration rate (MDRD); HDL, high density lipoprotein; NS, not significant; SBP, systolic blood pressure; UAE, urinary albumin excretion. In case of skewed distribution, data were Ln-transformed to obtain normal data distribution. A negative standardized beta indicates that the higher the value of the variable under study, the more negative the slope of renal function over time is. CRP, hs C-reactive protein; eGFR, estimated glomerular filtration rate (MDRD); HDL, high density lipoprotein; NS, not significant; SBP, systolic blood pressure; UAE, urinary albumin excretion. In case of skewed distribution, data were Ln-transformed to obtain normal data distribution. A negative standardized beta indicates that the higher the value of the variable under study, the more negative the slope of renal function over time. Tables 4 and 5 present the results of the gender-specific multivariate linear regression models. A higher (absolute) standardized beta value indicates a stronger association between the independent variable and the outcome change in eGFR over time. In males, a higher systolic blood pressure, plasma glucose, and UAE were associated with more renal function decline. In contrast, a higher waist circumference and cholesterol/HDL ratio were associated with less renal function decline over time. The quadratic terms of UAE and cholesterol/HDL ratio were significant in the linear regression model. In females, results were slightly different, insofar that only systolic blood pressure, plasma glucose, and cholesterol/HDL ratio were associated with more renal function decline, whereas triglycerides were found to be associated with less renal function decline. In this model, inclusion of the quadratic term of SBP was significant.Table 4Multivariate model for males explaining change in renal function during follow-up (assessed as slope through three eGFR values over time per individual)Male (N=2770)Standardized betaP-valueLn_UAE2−0.581<0.001Cholesterol/HDL ratio20.129<0.001Waist circumference0.102<0.001Glucose−0.096<0.001SBP−0.0640.003eGFR, estimated glomerular filtration rate (MDRD); HDL, high-density lipoprotein; SBP, systolic blood pressure; UAE, urinary albumin excretion.Variables included in the multivariate prediction model are statistically significant associated with slope of renal function over time. The model is adjusted for baseline eGFR, age, and the use of medication. In case quadratic terms of variables proved to contribute significantly to the model (indicated with 2), the single term was also forced into the model. For reasons of clarity, only results with respect to the quadratic term are shown in the table. In case of skewed distribution, data were Ln-transformed to obtain normal data distribution. A negative standardized beta indicates that the higher the value of the variable under study, the more negative the slope of renal function over time. The variables are ranked on the order of the standardized beta. Open table in a new tab Table 5Multivariate model for females explaining change in renal function during follow-up (assessed as slope through three eGFR values over time per individual)Female (N=2718)Standardized betaP-valueSBP2−0.3590.026Glucose−0.0670.002Cholesterol/HDL ratio−0.0610.014Ln_Triglycerides0.0520.038eGFR, estimated glomerular filtration rate (MDRD); HDL, high-density lipoprotein; SBP, systolic blood pressure.Variables included in the multivariate prediction model are statistically significant associated with slope of renal function over time. The model is adjusted for baseline eGFR, age, and the use of medication. In case, quadratic terms of variables proved to contribute significantly to the model (indicated with 2), the single term was also forced into the model. For reasons of clarity, only results with respect to the quadratic term are shown in the table. In case of skewed distribution, data were Ln-transformed to obtain normal data distribution. A negative standardized beta indicates that the higher the value of the variable under study, the more negative the slope of renal function over time. The variables are ranked in order of the standardized beta. Open table in a new tab eGFR, estimated glomerular filtration rate (MDRD); HDL, high-density lipoprotein; SBP, systolic blood pressure; UAE, urinary albumin excretion. Variables included in the multivariate prediction model are statistically significant associated with slope of renal function over time. The model is adjusted for baseline eGFR, age, and the use of medication. In case quadratic terms of variables proved to contribute significantly to the model (indicated with 2), the single term was also forced into the model. For reasons of clarity, only results with respect to the quadratic term are shown in the table. In case of skewed distribution, data were Ln-transformed to obtain normal data distribution. A negative standardized beta indicates that the higher the value of the variable under study, the more negative the slope of renal function over time. The variables are ranked on the order of the standardized beta. eGFR, estimated glomerular filtration rate (MDRD); HDL, high-density lipoprotein; SBP, systolic blood pressure. Variables included in the multivariate prediction model are statistically significant associated with slope of renal function over time. The model is adjusted for baseline eGFR, age, and the use of medication. In case, quadratic terms of variables proved to contribute significantly to the model (indicated with 2), the single term was also forced into the model. For reasons of clarity, only results with respect to the quadratic term are shown in the table. In case of skewed distribution, data were Ln-transformed to obtain normal data distribution. A negative standardized beta indicates that the higher the value of the variable under study, the more negative the slope of renal function over time. The variables are ranked in order of the standardized beta. Figure 1 presents the graphical interpretation of the associations between independent variables and eGFR slope that were identified by multivariate regression analysis. More renal function decline is observed in the higher range of systolic blood pressure, glucose, and UAE, both in males and in females. The curves for cholesterol/HDL ratio and waist circumference versus change in eGFR over time, however, show opposite patterns for males and females. A priori-defined sensitivity analyses were performed. To investigate whether inclusion of only subjects with reliable slopes influences the results, we excluded the 773 males and 812 females with observed eGFR values that were not within the 99% confidence interval of the expected eGFR value. The results obtained were only slightly different. In males, the cholesterol/HDL ratio was not significantly associated with change in renal function, whereas in females, only triglycerides were not found to be associated with outcome anymore. The sensitivity analysis performed with a mixed effects model with random intercepts and random slopes resulted in models with the same variables included. Additionally, we investigated the potential role of hormonal status. For this purpose, we repeated the multivariate linear regression analysis only in postmenopausal females (N=1107). Similar results were obtained as in the overall group of females. Furthermore, we performed an analysis using a relative instead of absolute measure for renal function decline and an analysis using slopes through the reciprocals of serum creatinine values as outcome variables. The results of these analyses were essentially similar to our primary analyses, as were the results of the analyses performed in a subcohort representative for the general population. In this study, we investigated which modifiable risk factors are associated with change in renal function during follow-up in a community-based study cohort. We found different results for males versus females. In males, UAE was the strongest independent predictor of greater renal function decline, together with plasma glucose and systolic blood pressure. In contrast, waist circumference and cholesterol/HDL ratio were associated with a better renal function outcome. In females, systolic blood pressure and plasma glucose were independent risk predictors of renal function decline, whereas triglycerides were associated with better renal prognosis. The interest in identification of modifiable risk factors of renal function decline is increasing. Such risk factors may be used to estimate a subject's risk of future renal function decline and may also form the basis for preventive intervention. The mean eGFR decline we found in this study is low, probably not pathological and does not warrant intervention. However, the goal of this study was to identify predictors of accelerated renal function loss. Most observational studies investigating this issue apply 'threshold' analysis, using a cut-off value to indicate that subjects reach a certain stage of CKD. Most common cut-off values are the incidence of ESRD (defined as start of renal replacement therapy) or de novo K/DOQI CKD stage 3 or 4 (defined as eGFR below 60 or 30 ml/min/1.73 m2).9.Fox C.S. Larson M.G. Leip E.P. et al.Predictors of new-onset kidney disease in a community-based population.JAMA. 2004; 291: 844-850Crossref PubMed Scopus (915) Google Scholar,10.Ishani A. Grandits G.A. Grimm R.H. et al.Association of single measurements of dipstick proteinuria, estimated glomerular filtration rate, and hematocrit with 25-year incidence of end-stage renal disease in the multiple risk factor intervention trial.J Am Soc Nephrol. 2006; 17: 1444-1452Crossref PubMed Scopus (212) Google Scholar,11.Gelber R.P. Kurth T. Kausz A.T. et al.Association between body mass index and CKD in apparently healthy men.Am J Kidney Dis. 2005; 46: 871-880Abstract Full Text Full Text PDF PubMed Scopus (359) Google Scholar,12.Hsu C.Y. McCulloch C.E. Darbinian J. et al.Elevated blood pressure and risk of end-stage renal disease in subjects without baseline kidney disease.Arch Intern Med. 2005; 165: 923-928Crossref PubMed Scopus (307) Google Scholar This study applies a 'slope' analysis. The choice of slope versus threshold analysis has received scant attention, but has important implications. This is illustrated by the following theoretical example. It is known that in obese subjects GFR values estimated with the modification of diet in renal disease (MDRD) formula are considerably lower than their true GFR because, in general, obesity is associated with more muscle mass.13.Verhave J.C. Fesler P. Ribstein J. et al.Estimation of renal function in subjects with normal serum creatinine levels: influence of age and body mass index.Am J Kidney Dis. 2005; 46: 233-241Abstract Full Text Full Text PDF PubMed Scopus (331) Google Scholar Therefore, obese subjects at similar baseline true GFR and at similar rate of true GFR loss as nonobese subjects will reach an MDRD formula-based eGFR threshold of 30 or 60 ml/min/1.73 m2 earlier than their nonobese counterparts. This suggests that obesity is a risk factor for renal function decline, whereas a slope analysis would not have led to this conclusion. One might consider that application of an eGFR-independent threshold, such as the occurrence of ESRD, might circumvent this problem. However, obesity has been found to be associated with better survival in subjects in renal replacement therapy.14.Kalantar-Zadeh K. Kopple J.D. Obesity paradox in patients on maintenance dialysis.Contrib Nephrol. 2006; 151: 57-69Crossref PubMed Scopus (122) Google Scholar In case this would also be true for K/DOQI CKD stage 4, obese subjects would survive 'preferentially'. This will result in the observation that the proportion of obese subjects that reaches ESRD is higher than in the general population, again leading to the possible incorrect conclusion that obesity is associated with worse renal function outcome. For these reasons, together with the fact that we wanted to study risk factors of renal function decline over the entire eGFR range, we adopted a slope-based analysis with change in renal function during follow-up as outcome parameter. We also performed our analyses using slopes based on the reciprocals of serum creatinine values and using relative change in eGFR as outcome parameters. These analyses resulted in the identification of the same predictors, making our results convincing. Applying a slope-based analysis, we found in both males and females higher systolic blood pressure and higher plasma glucose to be major determinants of change in renal function. This is in line with other studies investigating community-based populations, but applying threshold analysis. High plasma glucose has been shown to be a risk factor of the development of CKD15.Fox C.S. Larson M.G. Leip E.P. et al.Glycemic status and development of kidney disease: the Framingham Heart Study.Diabetes Care. 2005; 28: 2436-2440Crossref PubMed Scopus (155) Google Scholar and ESRD.16.Iseki K. Ikemiya Y. Kinjo K. et al.Prevalence of high fasting plasma glucose and risk of developing end-stage renal disease in screened subjects in Okinawa, Japan.Clin Exp Nephrol. 2004; 8: 250-256Crossref PubMed Scopus (21) Google Scholar The same holds true for high blood pressure.12.Hsu C.Y. McCulloch C.E. Darbinian J. et al.Elevated blood pressure and risk of end-stage renal disease in subjects without baseline kidney disease.Arch Intern Med. 2005; 165: 923-928Crossref PubMed Scopus (307) Google Scholar,17.Tozawa M. Iseki K. Iseki C. et al.Blood pressure predicts risk of developing end-stage renal disease in men and women.Hypertension. 2003; 41: 1341-1345Crossref PubMed Scopus (233) Google Scholar,18.Yamagata K. Ishida K. Sairenchi T. et al.Risk factors for chronic kidney disease in a community-based population: a 10-year follow-up study.Kidney Int. 2006; 71: 159-166Abstract Full Text Full Text PDF PubMed Scopus (392) Google Scholar,19.Iseki K. Iseki C. Ikemiya Y. et al.Risk of developing low glomerular filtration rate or elevated serum creatinine in a screened cohort in Okinawa, Japan.Hypertens Res. 2007; 30: 167-174Crossref PubMed Scopus (20) Google Scholar Interestingly, similar to our study, a study performed in Maryland, USA, showed in both males and females a strong relationship between systolic blood pressure and the development of CKD, with the relationship being strongest in females and the cumulative incidence of ESRD increasing exponentially in the more severe stages of hypertension.20.Haroun M.K. Jaar B.G. Hoffman S.C. et al.Risk factors for chronic kidney disease: a prospective study of 23,534 men and women in Washington County, Maryland.J Am Soc Nephrol. 2003; 14: 2934-2941Crossref PubMed Scopus (382) Google Scholar Of note, we found a difference of 10 mmHg in systolic blood pressure levels between males and females. This result is in line with other community-based studies.21.Primatesta P. Poulter N.R. 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Although most evidence on the impact of urinary albumin leakage and renal prognosis is based upon data on overt proteinuria in subjects with nondiabetic25.Ruggenenti P. Perna A. Mosconi L. et al.Urinary protein excretion rate is the best independent predictor of ESRF in non-diabetic proteinuric chronic nephropathies. 'Gruppo Italiano di Studi Epidemiologici in Nefrologia' (GISE
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