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Saudi Journal of Kidney Diseases and Transplantation
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Year : 2011  |  Volume : 22  |  Issue : 5  |  Page : 1055-1063
Egypt information, prevention, and treatment of chronic kidney disease (EGIPT-CKD) programme: Prevalence and risk factors for microalbuminuria among the relatives of patients with CKD in Egypt

1 Department of Nephrology, Damanhour Medical National Institute, General Organization of Teaching Hospitals and Institutes, Ministry of Health, Egypt
2 Sheffield Kidney Institute, The University of Sheffield, Sheffield, United Kingdom

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Date of Web Publication6-Sep-2011


Chronic kidney disease (CKD) is increasingly recognized as a public health problem, and is linked to the risk of development of cardiovascular disease (CVD) and end-stage renal disease (ESRD) with their attendant morbidity, mortality and increased healthcare costs. There is still paucity of data on the prevalence and risk factors for microalbuminuria (MA) and CKD in the Middle East. We report a cross-sectional study of the prevalence and risk factors for MA in the relatives of patients with CKD from a community-based screening programme in Egypt. The study was conducted among participants of the Egypt Information, Prevention, and Treatment of Chronic Kidney Diseases (EGIPT-CKD) Program, a population-based screening program for MA and CKD in Damanhour, Egypt. The screening tools included a questionnaire collating information on demographics, lifestyle, medical and family history of diabetes mellitus, hypertension and CKD. The prevalence of MA was 10.6% in the population screened. The prevalence was 6.2% in the non-diabetic and non-hypertensive subjects. The prevalence of albuminuria increases with age (P = 0.001 for trend). The prevalence was higher in the subjects with diabetes, hypertension, obesity or CVD. There was also a higher burden of MA subjects with low educational attainment (16% vs 5.6%; P = 0.001) and also those with a positive history of smoking (15.7% vs 8.1%; P = 0.01). The independent predictor variables associated with the presence of MA in a mutually adjusted logistic regression model were age (OR = 1.055, 95% CI: 1.01-1.10), mean arterial blood pressure (OR = 1.04, 95% CI: 1.102-1.07) and personal history of CVD (OR = 2.34, 95% CI: 2.31-18.1). In this study, we determined the prevalence and risk factors for those having MA among the first-degree relatives of ESRD patients of the EGIPT-CKD program in Damanhour, Lower Egypt.

How to cite this article:
Gouda Z, Mashaal G, Bello AK, El Attar A, El Kemmry T, El Reweny A, El Nahas M. Egypt information, prevention, and treatment of chronic kidney disease (EGIPT-CKD) programme: Prevalence and risk factors for microalbuminuria among the relatives of patients with CKD in Egypt. Saudi J Kidney Dis Transpl 2011;22:1055-63

How to cite this URL:
Gouda Z, Mashaal G, Bello AK, El Attar A, El Kemmry T, El Reweny A, El Nahas M. Egypt information, prevention, and treatment of chronic kidney disease (EGIPT-CKD) programme: Prevalence and risk factors for microalbuminuria among the relatives of patients with CKD in Egypt. Saudi J Kidney Dis Transpl [serial online] 2011 [cited 2021 May 17];22:1055-63. Available from: https://www.sjkdt.org/text.asp?2011/22/5/1055/84570

   Introduction Top

The worldwide rise in the number of patients with chronic kidney disease (CKD) and consequent end-stage renal disease (ESRD) necessitating renal replacement therapy (RRT) and attendant cardiovascular disease (CVD) is threatening to reach epidemic proportions over the next decade, and only a small number of countries have robust economies able to meet the challenges posed. [1],[2],[3] In Egypt, one of the developing countries, poverty has emerged as one of the most challenging socio-economic problems, with 22.9% of the total populations within the national poverty line. [4] A change in global approach to CKD from treatment of ESRD to much more aggressive primary and secondary prevention is therefore imperative. [1]

A number of population-based studies are conducted on CKD and its determinants in many parts of the World. Such studies are limited in the Middle East and Arab World. The Egypt Information, Prevention, and Treatment of Chronic Kidney Diseases (EGIPT-CKD) programme is a community-based mass screening program carried out among a population group at high-risk for the development of CKD and CVD such as diabetics, hypertensives and subjects with family history of diabetes, hypertension, CVD and CKD in Damanhour city and the surroundding towns in Al-Buhayrah governorate, in Lower Egypt.

This paper reports the prevalence estimates and risk factors for microalbuminuria (MA) in a group of first-degree relatives of patients on our ESRD programme in Damanhour Medical National Institute (DMNI), Egypt.

   Methods Top

Design and setting

The EGIPT-CKD project is a community-based mass screening program carried out among the population groups at high-risk for the development of CKD and CVD, including participants with personal history of diabetes mellitus, hypertension and/or CVD, participants with family history of diabetes, hypertension and/or CVD and the first-degree relatives of ESRD patients in Damanhour city and the surrounding towns in Al-Buhayrah governorate, in the north of Egypt. It is a cross-sectional study designed to investigate the prevalence and risk factors for CKD in these population groups.

Study population and recruitment

The study started in November 2006, by contacting all patients on the ESRD programme in DMNI, Egypt. They were informed about the purpose of the project and the benefits of early detection of CKD and its modifiable risk factors in their families. This was achieved by health educational meetings and brochures in traditional Arabic language targeting the general community members. All the ESRD patients were asked to invite their adult first-degree relatives for participation in the project by giving them brochures, information leaflets and letters of invitation to participate in the project. All first-degree relatives interested were asked to contact the investigators at DMNI. About 94% of the patients contacted forwarded names of their relatives for participation. The remaining had no relatives or relatives not interested in participating.

Names of 1,087 individuals were returned from the individual families, between October 2006 and February 2007. Of these, 404 were excluded as age <18 years (n = 150), pregnant (n = 4) and non-relatives (n = 250) [Figure 1].
Figure 1: Recruitment flowchart.

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The remaining 683 who satisfied the following inclusion criteria were enrolled in the study:

  • Age-18 years or older
  • Family history of ESRD
These subjects (n = 683) consented for involvement in the study and were given a questionnaire, information leaflets and a vial to collect an early morning urine sample along with relevant instructions. Of these subjects, 417 completed the screening programme and were therefore included in this analysis. Data on the remaining subjects is currently being collated [Figure 1].

Each participant provided informed consent before inclusion in the project. Research governance and ethical approval were obtained from the Institutional Review Board (IRB), Human Studies Committee, Ain Shams University, Cairo, Egypt, and from the Human Research Ethics Committee in the General Organization of Teaching Hospitals and Institutes, Egyptian Ministry of Health, Cairo, Egypt.

Data collation and analysis

Each participant filled an investigator-adminis tered questionnaire. The questionnaire was administered to each subject by one of the study investigators (ZG, GM, AA). The questionnaire was adapted from the ISN-COMGAN KHDC programme on chronic non-communicable diseases. [5] It was piloted and validated to our setting. It contained questions on the following: socio-demographic (age, gender and educational status), smoking, personal and family health and lifestyle history (diabetes, hypertension, CVD and CKD), area of residence (rural or urban Egypt), levels of physical activity, dietary habits, income levels, employment status, health insurance and access to family doctor.

Age was categorized using standard method. [6] Educational achievement was grouped into two categories of low (<10 years) and high levels (>10 years) of educational attainment according to the years spent in full-time education. Diabetes was defined by a personal history of diabetes mellitus and/or diabetic medication usage or by fasting glucose levels by standard criteria. [6],[7] Similarly, hypertension was defined by personal history of hypertension and/or use of anti-hypertensive agents or blood pressure levels according to the standard criteria. [6],[7] A history of CVD was defined as any of coronary heart disease, stroke or peripheral vascular disease. Family history of diabetes or hypertension was taken as reported. Smoking status was categorized as current smoker (yes/no). Residential status was classified as rural (living outside the city of Damanhour) and urban (living within Damanhour).

Exposure measurements

All subjects were seen at the screening facility at DMNI, and anthropometric measurements were performed (including weight, height and waist and hip circumferences). After removal of shoes and heavy clothing, weight was measured to the nearest 0.5 kg. Height and waist circumference were measured to the nearest 0.5 cm.

Blood pressure measurements were performed using standard guidelines with an Erkameter 3000 mercurial sphygmomanometer (Williams Medical Supplies, Rhymney, UK). Systolic and diastolic blood pressure were measured on three occasions for subjects without history of hypertension.

Fasting blood samples were taken for measurements of serum cholesterol, triglycerides, serum creatinine, plasma glucose and hemoglobin. Subjects were asked to bring urine samples on a visit to the screening site. The subjects received instructions on how to collect a urine sample and to postpone collection in the event of fever, urinary tract infection, menstruation or heavy exercise.

Laboratory methods

The biochemical measurement of plasma glucose, serum creatinine and HbA1c and lipid profile were performed using standard methods with the use of a Hitachi 912 auto-analyser (Boehringer Mannheim Diagnostics, Indianapolis, IN, USA).

Urinary albumin measurement and evaluation

Urinary albumin concentration was determined by nephelometry with a threshold of 10 mg/L and intra-assay and inter-assay coefficients of variation of 2.6% and 2.2%, respectively.

Urinary creatinine was measured by a Hitachi 912 autoanalyzer (Boehringer Mannheim Diagnostics).

Urinary albumin excretion is expressed as albumin-creatinine ratio (ACR) using standard guidelines. The albumin (mg/dL)/creatinine (g/dL) ratio (ACR) was calculated for every participant, with an ACR of >30 mg/gm defined as microalbuminuria, and this confirmed as per standard guidelines. [6],[7]

   Definitions Top

CKD was defined as an estimated glomerular filtration rate (eGFR) of <60 mL/min/1.73 m. [6],[7]

MA was defined as persistent elevation of urinary albumin excretion as an ACR of >30 mg/gm in at least two out of three urine testings within a period of three months. [7]

Hypercholesterolemia was defined as cholesterol ≥200 mg/dL and hypertriglyceridaemia was defined as triglycerides ≥150 mg/dL.

   Statistical Analysis Top

All analyses and calculations were performed using the SPSS statistical package, version 15.0 (SPSS Inc., Chicago, IL, USA). Descriptive analyses were used to characterize the participants by socio-demographic, lifestyle and clinical factors. Continuous data were presented as mean ± SD and as proportions for categorical variables. Prevalence of MA was expressed as percentages. Independent sample t-tests were applied for comparison of group means, and chi-squared tests applied for proportions. Binomial logistic regression analyses were used to assess relationships between screened population demographic, health and lifestyle characteristics with the presence of MA and CKD. Factors associated with MA were first determined using univariate logistic regression analysis. Variables significant at a P-value of <0.050 on univariate analysis were presented further for the multivariate logistic regression model. Adjustments were made in the multivariate model for minimize confounding. A two-sided P-value of <0.05 was considered statistically significant.

   Result Top

General characteristics

The overall mean age of the participants was 39 ± 14.3 years. 43.2% were males. 68.7% were of rural residence. 48.4% reported low educational attainment. Twenty-five percent and 10% were hypertensives and diabetics, respectively.

Only 3.4% reported a personal history of CVD. Majority (84.6%) reported a family history of hypertension, while about half of the participants did report a family history of diabetes or CVD. The overall Body Mass Index was 29.9 ± 6.2 kg/m[2] , and 46.7% were obese. Socio-demographic and health characteristics of the study population are depicted in [Table 1].
Table 1: Socio-demographics and health characteristics of the study population (N = 417).

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Overall prevalence of microalbuminuria

Overall, 42 subjects out of the total screened population of 417 participants in the study had MA, giving a prevalence of 10.6%. [Table 2] depicts the distribution of MA across the population categories.
Table 2: Distribution of albuminuria across socio-demographic and clinical characteristics.

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The prevalence of MA across the various age categories shows an increasing trend (P = 0.001). No significant differences across the prevalence of MA with gender (P = 0.43) were noted.

There was a decreasing trend in the prevalence of MA with increasing levels of educational attainment. MA distribution by the two classes of educational level was 16.0% in those with low-level educational attainment and 5.6% in those with a high-level education (P = 0.001).

Population characteristics of the study participants across the two outcomes categories of the presence/absence of MA is depicted in [Table 3]. The subjects with MA were more elderly, obese, smokers, hypertensives and had a higher prevalence of low education and personal history of CVD [Table 3].
Table 3: Socio-demographic and health characteristics of the study population by classes of albuminuria.

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Regression model analysis

The independent predictor variables associated with the presence of MA in a mutually adjusted logistic regression model are shown in [Table 4]; age (OR = 1.055, 95% CI: 1.01-1.10), mean arterial blood pressure (OR = 1.04, 95% CI: 1.102-1.07) and personal history of CVD (OR = 2.34, 95% CI: 2.31-18.1).
Table 4: A mutually adjusted logistic regression mode for the independent predictor variables associated with the presence of MA.

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   Discussion Top

This is the first study to our knowledge that specifically screens the first-degree relatives of patients being treated for CKD in the Middle East and North Africa for the presence of MA. A number of studies have evaluated the prevalence of CKD among family members of patients with ESRD. [8],[9],[10],[11] One of such studies has shown that a family history of CKD in first-, second- or even third-degree relative was associated with a 13% higher risk of developing ESRD. [10] We extend these findings by investigating individuals with family history of CKD for MA in the Mediterranean city of Damanhour in Egypt.

Few studies in the Middle East have investigated the prevalence and determinants of MA in the communities. One of such studies is by Abo Zenah et al, which provided a first description of increased albuminuria levels in a small percentage of young adult Arab subjects from Saudi Arabia, and in that study a similar prevalence for MA as in this study was reported. [12] This Saudi study is limited by the fact that it is a selective screening process carried out on potential army recruits and is thus not strictly a community-based programme.

Our results indicate that MA is more common in the elderly, with the prevalence showing an increasing trend with aging, and we have found age to be an independent determinant of MA. This was similar to the findings in some other epidemiological studies. [13],[14],[15],[16],[17] The higher prevalence of MA in this study in the diabetics, hypertensives, obese and subjects with CVD is also consistent with findings in these other studies. [13],[14],[15],[16],[17]

Another interesting finding in this study is the higher prevalence of MA in participants with low levels of educational attainment. This needs further and intensive evaluation as a recent study from the US showed that socio-economic factors could modify MA distribution in the general population. [18] The study in the US showed a relationship between federal poverty levels with MA, but only in an ethnic minority population; whereas in this study, we have not examined the effects of race as our population is homogenously Arabian.

The strengths of our study are that first, the study population was a generated sample of a general population based in the same community. Second, the population was a homogenous population. Third, the response rate to the study was reasonable. [19] Fourth, we have used ACR in the definitions of MA. ACR has good reliability and has been recommended for population screening. [20] Moreover, we have used standard techniques for the measurement of MA, with repeated screenings as recommended by the various guidelines.

We corrected for some potential variability in urine concentration by factoring for urinary creatinine excretion and have used ACR in the analysis. Studies have shown that early morning spot urine gives a reasonable estimate of the 24-hour urinary excretion of albumin and has been shown to be a reliable index of albuminuria in population-based studies. [20]

In addition, we have not relied on self-reported information on the various demographic and clinical parameters evaluated, as in most similar epidemiological surveys. Self-reported histories have limitations because of the possibility of misclassification.

Our limitations are that we lacked data on other CVD risk markers such high-sensitivity CRP (hs-CRP), and we have not matched the study subjects with a control group from the population in the community without family history of CKD. However, we have controlled for other potential confounding variables such as diabetes, hypertension and smoking in the regression analysis.

Another limitation is that we have not examined the impact of infections and infestations on albuminuria that may confound our findings.

Epidemiologic and clinical significance of our study stems from the fact that the early detection and prevention of early markers of CKD and CVD risk such as MA has been emphasized in the various guidelines and recommendations. [6],[7] This is all the more relevant in individuals with increased risk such as those with family history of CKD. To our knowledge, this is the first population-based study that has examined the distribution and determinants of MA in this group in the whole of Africa and the Middle East. Our findings may inform the current debate regarding the cost-effectiveness of whole population screening compared with targeted screening of those at increased risk such as the relatives of CKD patients, diabetics, hypertensives and elderly in our communities. This may allow early intervention aimed at alleviating the growing burden of CKD and the associated CVD morbidity and mortality. From our data, emphasis should be on screening those with potential risk factors such as relatives of CKD patients with hypertension and diabetes, and the elderly In conclusion, we report in this the prevalence estimates and risk factors for those with MA among the relatives of ESRD patients of the EGIPT-CKD programme from the Damanhour city in the Lower Egypt

   Acknowledgments Top

This work has been made possible partly through Dr. Zaghloul Gouda, ISN-funded fellowship training in Sheffield Kidney Institute, ISN COMGAN Research and Prevention committee, KHDC program grant and The Egyptian Society for caring of renal patients award. We would like to express our thanks to Prof. Rashad Barsoum, Prof. A. Meguid El Nahas and Prof. Zakaria El Baz for their unlimited support to the EGIPT CKD Programme. Finally, thanks are due to all members of the Nephrology Department in Damanhour Medical National Institute, Egypt, who do their best for early detection and prevention of kidney diseases in their community.

   References Top

1.el Nahas AM, Bello AK. Chronic kidney disease. The global challenge. Lancet 2005;365:331-40.  Back to cited text no. 1
2.Xue JL, Ma JZ, Louis TA, Collins AJ. Forecast of the number of patients with end stage renal disease in the united states to the year 2010. J Am Soc Nehprol 2001;12:2753-8.  Back to cited text no. 2
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5.Schoolwerth AC, Engelgau MM, Hostetter TH, et al. Chronic kidney disease: A public health problem that needs a public health action plan. Prev Chronic Dis 2006;3(2):A57.  Back to cited text no. 5
6.Anonymous. K/DOQI Clinical Practice Guidelines for Chronic Kidney Disease, Evaluation Classification and stratification. Kidney Disease Outcome Quality Initiative. Am J Kidney Dis 2002;39(Suppl 2):S1-246.  Back to cited text no. 6
7.Levey AS, Atkins R, Coresh J, et al. Chronic kidney disease as a global public health problem: approaches and initiatives - a position statement from Kidney Disease Improving Global Outcomes. Kidney Int 2007;72:247-59.  Back to cited text no. 7
8.Ferguson R, Grim CE, Opgenorth TJ. A familial risk of chronic renal failure among blacks on dialysis? J Clin Epidemiol 1988;41:1189-96.  Back to cited text no. 8
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10.Marcantoni C, Brezzi B, Matalone M, et al. Increased risk of renal abnormalities in relatives of end-stage renal disease (ESRD) patients: A case control study. J Am Soc Nephrol 2001;12:226A (abstract).  Back to cited text no. 10
11.Bello AK, Peters J, Wight J, de Zeeuw D, El Nahas M. A population-based screening for microalbuminuria among relatives of CKD patients: the Kidney Evaluation and Awareness Program in Sheffield (KEAPS). Am J Kidney Dis 2008;52:434-43.  Back to cited text no. 11
12.Abo-Zenah H, El-Benayan A, El Nahas AM. Prevalence of increased albumin excretion rate in young Saudi adults. Nephron Clin Pract 2008;108(2):c155-62.  Back to cited text no. 12
13.Cirillo M, Senigalliesi L, Laurenzi M, et al. Microalbuminuria in nondiabetic adults: relation of blood pressure, body mass index, plasma cholesterol levels, and smoking: The Gubbio Population Study. Arch Intern Med 1998;158: 1933-9.  Back to cited text no. 13
14.Kramer H, Luke A, Bidani A, et al. Obesity and prevalent and incident CKD: The hypertension detection and follow up program. Am J Kidney Dis 2005;46:587-94.  Back to cited text no. 14
15.Fox CS, Larson MG, Leip EP, et al. Predictors of new-onset kidney disease in a community-based population. JAMA 2004;291:844-50.  Back to cited text no. 15
16.Valensi P, Assayag M, Busby M, et al. Microalbuminuria in obese patients with or without hypertension. Int J Obes Relat Metab Disord 1996;20:574-9.  Back to cited text no. 16
17.Bonnet F, Marre M, Halimi JM, et al. Waist circumference and the metabolic syndrome predict the development of elevated albuminuria in non-diabetic subjects: the DESIR Study. J Hypertens 2006;24:1157-63.  Back to cited text no. 17
18.Martins D, Tareen N, Zadshir A, et al. The association of poverty with the prevalence of albuminuria: data from the Third National Health and Nutrition Examination Survey (NHANES III). Am J Kidney Dis 2006;47:965-71.  Back to cited text no. 18
19.Okura Y, Urban LH, Mahoney DW, Jacobsen SJ, Rodeheffer RJ. Agreement between self report questionnaires and medical record data was substantial for diabetes, hypertension, myocardial infarction and stroke but not for heart failure. J Clin Epidemiol 2004;57:1096-103.   Back to cited text no. 19
20.20. Gansevoort RT, Verhave JC, Hillege HL, et al. The validity of screening based on spot morning urine samples to detect subjects with microalbuminuria in the general population. Kidney Int 2005;Suppl:S28-35.  Back to cited text no. 20

Correspondence Address:
Zaghloul Gouda
Department of Nephrology, Damanhour Medical National Institute, General Organization of Teaching Hospitals and Institutes, Ministry of Health
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PMID: 21912051

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  [Table 1], [Table 2], [Table 3], [Table 4]

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