Determining the prevalence of risk factors of chronic kidney disease in the United Arab Emirates population

Results from the pilot phase of the community screening program
Determining the prevalence of risk factors of chronic kidney disease in the United Arab Emirates population

Correspondence

Dr Manu Gopala Krishnan, Specialist,

Department Of Nephrology, Aster

Hospital, Dubai, UAE, 9 A Street, Al Qusais,

Dubai – United Arab Emirates

E: [email protected]

T: +971 4 4 400 500

Funding information

This study was funded by

Aster Hospital Dubai.

ABSTRACT

There is limited data available about the prevalence of chronic kidney disease (CKD) and its risk factors in the general population of The United Arab Emirates (UAE). To estimate the prevalence of CKD and its associated risk factors in the UAE, which has a predominately expatriate population, we conducted a pilot community-based screening program in two hospitals in Dubai, taking blood and urine samples for analysis. The sample included 491 adults (75.7% were males), predominantly expatriates with Indian (61.9%), Pakistani (10.7%) and Filipino (10.6%) nationality. The mean age was 37.0 ± 11.3 years. Multivariate regression was used to establish correlations between eGFR, bioindicators of renal dysfunction and demographic data. The overall prevalence of low eGFR (<60) was 0.92% and 0.76% using the MDRD-3 and CKD-EPI glomerular filtration equations, respectively, but the prevalence of microalbuminuria was much higher (13.61%), giving an estimate of high CKD risk (combined low eGFR or microalbuminuria) of 13.76%. Male gender and increased age were significant predictors of low eGFR. We recorded pyuria in 65.51% of patients, haematuria in 6.89% and glycosuria in 11.62% despite the patients being symptomatic. Pyuria incidence was particularly high in the young and elderly, and may point to early urine infection, renal calculi, or poor water intake.

INTRODUCTION

Chronic Kidney Disease (CKD) has a global prevalence of approximately 11-13% (1), and is a key health indicator, being intrinsically linked to comorbidities including diabetes and cardiovascular disease (2). CKD incidence has increased by an estimated 32% globally between 2005 and 2015, and in many populations, it is expected to continue to rise (3). The true incidence and prevalence of CKD within a community are difficult to ascertain, because early to moderate CKD is usually asymptomatic. However, various epidemiologic studies suggest a prevalence of CKD ranging from 7% to 14% in various populations (1).

Albuminuria (mostly microalbuminuria or A2) has been reported in 7-10% of patients in the USA (3,4) and as many as 19.5% of patients in China (5). In the USA, glomerular filtration rate (GFR) falls below 60 ml/min/1.73 m2 in approximately 3% to 5% of patients (4), however no population level data is available detailing the prevalence of low eGFR or CKD in the United Arab Emirates (UAE). The UAE is known to have a high prevalence of CKD risk factors including hypertension, but previous studies indicate a prevalence of end stage renal failure (ESRF) that is lower than that of neighbouring countries (6). As 89% of the population are expatriates (7), studies reporting CKD prevalence in the Middle East and South East Asia are not necessarily comparable.

The three-year incidence of CKD levels 3-5 has been determined as 11.4% in a subgroup of UAE patients at high risk of cardiovascular disease (8), and the overall prevalence of CKD 3-5 was recorded as 3-5% in the Emirate of Abu Dhabi in 2011-2012 in patients presenting with symptoms prompting serum creatinine testing (9). Late presentation of CKD patients is currently typical in the UAE, which negatively impacts patient outcomes and increases costs (10).

Appropriate and timely lifestyle choices for persons with CKD can hamper the progression of kidney function deterioration as well as prevent the development or progression of CKD-related diseases (10), but this is only possible if patients are aware of their condition and if high risk subgroups of the population can be identified and encouraged to attend monitoring. Establishing a picture of renal health in countries such as the UAE is therefore an immediate priority (6).

A pilot study to follow the prevalence of protein uria, haematuria, and low estimated GFR (eGFR) was carried out in the UAE in volunteers undergoing routine testing in response to a CKD awareness campaign for renal testing. We report the baseline creatinine, eGFR and albuminuria results of the study participants alongside other bioindicators of CKD risk.

MATERIALS AND METHODS

Patient selection Patients were eligible for inclusion in the study if they volunteered for routine testing in response to a CKD awareness campaign at Aster Hospital Al Mankhool (West Dubai) & Aster Hospital Al Qusais (East Dubai). All tests were recorded in March-April 2019. Nationality was declared by all patients but one, who was omitted from the quantitative analysis, along with 9 further patients who were missing partial test data. The dataset of patients with all tests completed contained a total of 654 patients. Patients with hyperglycaemia were advised regarding lifestyle modifications and regular follow-ups to evaluate the difference.

Statistical methods

For patients for whom more than one mean daily serum creatinine value was recorded, the mean daily creatinine for the first day of presentation was used in the analysis to avoid bias towards patients requiring follow-up testing. For pus 1 (white blood cell) count values, test results recorded as cell count ranges of up to 5 (e.g. “0-2”) were assigned 0; higher cell count ranges were assigned the median bin value (e.g. 45 for “40-50”), results of “>100” and “50-170” were assumed equivalent and assigned the median value for the “50-170” bin (110). All cell count values over 170 were analysed as integer values. Patients with a pus 1 cell count of >5/mm3 were considered pyuric. Red blood cell (RBC) count results of “trace” and 1-3 were considered synonymous, as were “many” and 4-100, and “too numerous to count” and >100. Haematuria was defined as urine RBC count ≥3. Proteinuria (albuminuria) was recorded in all cases of presence of protein and glycosuria was recorded in all cases of presence of glucose.

eGFR was calculated using both the Chronic Kidney Disease Epidemiology Collaboration (CKDEPI) (10) and Modification of Diet in Renal Disease (MDRD) (11) formulas. For the purposes of adjusting for black African ethnicity within the eGFR calculations, we have assumed that the following nationalities fall within this group: Cameroonian, Comorian, Ethiopian, Kenyan, Malawian, Nigerian, Sudanese, Tanzanian, Ugandan, and Zimbabwean. In order to gain statistical power given the small numbers of individuals representing some nationalities, the following groupings were made to group most nationalities of fewer than five individuals and models repeated before and after grouping: North American (American and Canadian), Other European (Albania, Dutch, Italian, Serbian, Turkish, Uzbekistani), Western African (Nigerian, Cameroonian), Central to Southern African (Zimbabwean, Malawian), East African (Kenyan, Tanzanian, Ugandan, Ethiopian), and Middle Eastern (Lebanese, Jordanian, Syrian).

Generalised linear models (GLMs) were constructed to model eGFR as a response with national- ity, age, and sex as predictors, followed by creatinine ratio and continuous biomarker values (RBC, Pus 1) as responses with the same predictor variables. In order to analyse the RBC count based on the binned categories recorded, the four RBC level bins recorded (negative, trace, many, numerous) were assigned levels 0-3 and the variables were treated as continuous. To analyse glucose and protein results, the categories used to differentiate levels (Negative, trace, 1-4) were recoded as 0-5.

Serum creatinine derived indicators

eGFR generally decreased with age (p=2e-16) and was lower in men (p=8.6 e-14). As only five individu- als had a low mean daily CKD-EPI eGFR below 60, it was not feasible to categorically model eGFR indica- tive of compromised kidney function. However, all five participants with eGFR<60 were Indian, and four of these were female (Table 2). Further research will be needed to discern whether Indian women are generally at a higher risk of kidney impairment or whether this simply reflects the demographic split of patients.

Creatinine ratios were significantly lower in Egyptian participants (p=0.04) and Yemeni par- ticipants (p=0.001), and higher than average in East African patients (p=6e-04). In Yemeni patients, creatinine ratio decreased less rapidly with age (p=9e-04), and in East African patients, creatinine ratio decreased more rapidly with age (p=0.03). A single Indonesian patient had a remarkably high creatinine ratio (p=1.68e-05) and therefore also a high CKD-EPI eGFR (p=0.04).

Women had a 3-fold larger creatinine ratio (1/ creatinine) interquartile range than men (Figure 1, Table 2). Pakistani and East African women showed an increased creatinine ratio compared to men of the same nationalities (p=0.01, p=4e-04), but this gap narrowed with increasing age.

Urine test biomarkers

All patient prevalence of pyuria was 65.51%, haematuria prevalence was 6.89%, proteinuria prevalence was 13.61% and glycosuria prevalence was 11.62% (Table 2). Considering age and sex subgroups, sex was highly significant in predicting Pus 1 count (p=9.74e-10), with 86.79% of women having pyuria (Figure 2). A U-shaped relationship was evident between age and pyuria with highest prevalence in the elderly and the young (Table 3). Age was associated with significant increases in glucose level (p=6.0e-12) and in protein (albumin) level (p=0.05) (Table 3).

The only Emirati individual of the study had a significantly increased RBC count (P=3.8e-04), and the only Indonesian national had a significantly increased glucose level (p=0.002). These results should be interpreted with caution given that they reflect only single individuals.

DISCUSSION

The prevalence of CKD varied from 1.1% to 34.3% across various populations studied since 2000, with a global estimate of 11-13% (1). In the majority of previous studies, the prevalence of CKD increased with age within the same study populations (1), and, consistent with these findings, our model considering demographic variables with CKD-EPI eGFR shows a significant negative correlation between age and eGFR. The mean age of patients with CKD-EPI eGFR<60 in this study was 56.2 years ±15.0, compared to a whole study mean of 38.4 years ±10.8. The overall prevalence of low eGFR in the dataset was 0.76-0.92% depending on GFR formula. We observed a difference in the individuals indicated as having low GFR using the CKD-EPI and MDRD eGFR equations: among six individuals identified as having eGFR<60 with the MDRD equation (Table 2), one was classified as having an eGFR of ≥60 ml/min/1.73m2 with the CKD-EPI equation (CKD-EPI=68.14 ml/min/1.73m2, MDRD=59.18 ml/min/1.73m2). The mean eGFR of the whole cohort was 160.60 ml/min/1.73m2 using the MDRD formula and 124.79 ml/min/1.73m2 accord- ing to the CKD-EPI formula. Such discrepancies are not uncommon, with the CKD-EPI formula typically estimating higher GFRs in women and young people than the MDRD formula (13).

In this study, 13.6% of patients demonstrated proteinuria. Proteinuria is often the first indicator of progression towards renal failure (14). Only after a prolonged period of increasing proteinuria does the serum creatinine level begin to increase. Although proteinuria can be minimal in CKD, this pattern is commonly seen in CKD patients whose condition is progressing because of increased glomerulone- phritis (14). Glomerulonephritis is currently the leading cause of end stage renal failure in the UAE, followed by diabetes (6),

The prevalence of low eGFR that we observed may be lower than the population wide preva- lence, considering that the majority of patients were asymptomatic outpatients volunteering to access preventative healthcare and that CKD is currently most commonly diagnosed on emergency room presentation (10). However, we also recognise that some patients reporting low eGFR may have sustained acute kidney injuries that resolved soon after testing rather than progressing towards chronic disease. Overall CKD prevalence in the UAE is likely to be lower than the 11.4% reported CKD 3-5 incidence in patients with hypertension and/or cardiovascular disease, a high CKD risk subgroup (8). Comparing our low CKD-EPI eGFR prevalence (0.8%) to that of these patients (8.8%) confirms that the high cardiovascular risk cohort had atypically low eGFRs when compared to the general populus.

A number of studies report ‘CKD’ prevalence as albuminuria and/or a single eGFR measure- ment<60 (18,21). Our combined albuminuria and low CKD-EPI eGFR prevalence is 13.76%. Using this definition, ‘CKD’ prevalence in this cohort would be double that of Saudi Arabia and equivalent to that of China (Table 4). This value is considerably higher than the prevalence of low eGFR and it is therefore likely that the majority of UAE CKD cases qualify as having CKD based on having albuminuria before reaching low eGFR.

Sex-specific prevalence of low GFR

In most prior South Asian CKD prevalence studies (Table 4), the prevalence of CKD was greater in women than in men, across age categories and various ethnic groups. Our study results are consistent with these findings, with four of the five individuals identified with eGFR<60 being women. A sixth patient identified as having eGFR<60 using only the MDRD formula was also a woman.

Ethnicity-specific prevalence of low GFR

All five patients with low CKD-EPI eGFR were Indian, although a sixth patient identified as having eGFR<60 using only the MDRD formula was Pakistani. Both the CKD-EPI and MDRD formulas calculate eGFR differentially in black African and Caucasian patients, and it is arguable that these should be further developed and modified to reflect the baseline eGFRs of additional ethnic groups. There is therefore significant uncertainty as to how well eGFR reflects renal function in non-Caucasian patients (15).

Considering Indian patients, who made up the largest proportion of the cohort, Varma et al. (16) reported a high incidence of CKD (13-15%) in apparently healthy Indian subjects with a mean age of 36 years and no history of renal disease, a 3.95 prevalence of haematuria and a 9.9% prevalence of microalbuminuria, while The SEEK India cross- sectional study (17) recorded 17.2% CKD, 8.6% glycosuria, 19% haematuria and 13.7% proteinuria in the general population (Table 4). Our haematuria and proteinuria results for Indian patients are in- termediate to these two studies, but the glycosuria prevalence we recorded (11.6%) is higher than that of the SEEK study, potentially reflecting lifestyle differences.

Age and nationality-specific prevalence of renal dysfunction markers

There were age-based differences in how com- monly patients displayed renal decline symptoms. For example, all 6 individuals aged over 70 had pyuria, with Pus 1 counts of 43,000-44,000 (Table 2) and all 6 patients aged under 18 also had pyuria, creating a U-shaped relationship, which could potentially be explained by the vulnerability of young and old patients to urinary tract infections (UTIs). Increasing age was associated with a significant increase in urine glucose level (Table 3, p=4.2 e-12), and with progressive proteinuria (p=0.05).

Little variation was detected in renal dysfunction symptoms according to nationality, although this may reflect the small sample size. Although the overall prevalence of proteinuria (58%), haematuria (25%) and pyuria (75%) was atypically high in Egyptian patients (Table 3), this was explained when modelling nationality alongside sex, as there were more men in the Egyptian subgroup. Pyuria frequency was highest (80%) in the Pakistani patients and glycosuria in Sri Lankan patients (17%), but again these relationships were non-significant (Table 3).

It is likely that further links between renal dysfunction biomarkers and nationality and/or sex could be determined in the future, as more individuals from minority nationalities contribute their data to the project, and if more women can be recruited to the study. Extending the data capture will enable baseline values to be created for individual patients and for nationality groups to determine general or specific differences between patient groups. For example, there was low participation from individuals over 70 years, who are likely to be at higher risk of CKD (1), and significantly different values in some symptoms were observed for Indonesian and Emirati individuals, who represent ethnic groups in which limited population -level renal research has been conducted. CKD progres- sion speed typically positively correlates with age and male sex and varies by ethnicity (progression has been shown to be more rapid in non-Caucasian ethnicities in the West, including African Ameri- cans and Asians [South Asians and Pacific Asians]) (13). It is therefore imperative to encourage older people and those from ethnic minorities to attend screening.

<b>Figure 2</b><b><br></b>
Figure 2

The main observations of the study:

Most of the study group were of South Asian nationalities, including Indian (62%), Pakistani (11%) and Filipino (11%), and most were 18-50 years old (84%). Glycosuria was detected in 11.6% of the population studied. Proteinuria (albumin in the urine) was found in 87 patients (13.6% of the study sample), and microscopic haematuria in 45 (6.9%). Considering differences by nationality, asymp- tomatic Haematuria (blood in urine) was found in 11.4% of Pakistani participants and in 5.7% of Indians. The incidence of proteinuria was 17.1% vs 12.6% respectively. Most participants (65.1%) had pyuria (pus cells in urine), which was unexpected as most of them were asymptomatic. eGFR was found to be <60 ml/min/1.73m2 in only 6 people (0.9%) using the MDRD method and 5 (0.8%) using the CKD EPI formula. There were more women than men in this low eGFR group. Creatinine ratios were significantly lower in Egyptian participants (p=0.04) and Yemeni participants (p=0.001), and higher than average in East African patients (p=6e-04).

Limitations

CKD prevalence could not be assessed based on single measurements from the study patients, as CKD is defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria based on persistent low GFR (<60 mL/min/1.73 m2) and/or albuminuria over a period of at least three months (Levey et al 2012). Establishing CKD prevalence is a primary goal of this research programme as it continues. A further limitation of this study was that all participants with abnormal urine findings could not undergo detailed imaging and laboratory work to ascertain the cause of the findings.

CONCLUSIONS

The high incidence of pyuria in this study (65.1%) points towards the possibility of early urine infection, renal calculi, or poor water intake. It may also point towards occult infections of the genital tract . The female population is at a bigger risk for infection due to the shorter female urethra and may also be more prone to inadequate hydration. The incidence of hyperglycaemia was 11.6%. The prevalence of hyperglycaemia, lack of awareness about fluid intake, and inadequate personal hygiene may all have contributed to pyuria.

This study has helped to understand the need for frequent population screening to detect early onset of the chronic illnesses. Early detection would help to initiate life style modifications, which could help to retard the progression of major diseases. The importance of hydration among individuals needs to be emphasized; moreover, proper dietary habits and regular check- ups help to maintain the health of the general public. Women have an elevated risk of pyuria, low eGFR and therefore CKD, and should be encouraged to attend routine health screening.

REFERENCES:

  1. Hill NR, Fatoba ST, Oke JL, Hirst JA, O’Callaghan CA, Lasserson DS et al. Global Prevalence of Chronic Kidney Disease – A Systematic Review and Meta-Analysis. PLoS ONE 2016;11(7): e0158765.

  2. Liu M, Li XC, Lu L, Cao Y, Sun RR, Chen S, Zhang PY..Cardiovascular disease and its relationship with chronic kidney disease. Eur Rev Med Pharmacol Sci 2014;18(19):2918-26.

  3. Centers for Disease Control Chronic Kidney Disease Surveillance System. Available at https://nccd.cdc.gov/CKD/detail. aspx?Qnum=Q11 [Accessed 7th July 2019]

  4. Coresh J, Astor BC, Greene T, Eknoyan G, Levey AS. Prevalence of chronic kidney disease and decreased kidney function in the adult U.S. population: Third National Health and Nutrition Examination Survey. Am J Kidney Dis. 2003;41:1-12.

  5. Chen F, Yang WY, Wang JP, Jia WP, Ji LO, Xiao JZ et al. Albuminuria: Prevalence, associated risk factors and relationship with cardiovascular disease. J Diabetes Investig 2014;5(4):464-471.

  6. Farag YMK,Kari JA,Singh AK. Chronic Kidney Disease in the Arab World: A Call for Action. Nephron Clin Pract 2012;121:c120–c123.

  7. United Arab Emirates Government. Population and Demographic Mix. Available at https://www.government.ae/en/information- and-services/social-affairs/preserving-the- emirati-national-identity/population-and- demographic-mix [Accessed 7th July 2019]

  8. Al-Shamsi S, Regmi D, Govender RD. Chronic kidney disease in patients at high risk of cardiovascular disease in the United Arab Emirates: A population-based study. PLoS ONE 2018;13(6):e0199920.

  9. Richards N, Hassan M, Saleh AK, Dastoor H, Bernieh B, Abouchacra S, Jabri OA, Fleischmann A, Richards M, Marcelli D. Epidemiology and referral patterns of patients with chronic kidney disease in the Emirate of Abu Dhabi. Saudi J Kidney Dis Transpl 2015;26:1028-34.

  10. Howden EJ, Leano R, Petchey W, Coombes JS, Isbel NM, Marwick TH. Effects of Exercise and Lifestyle Intervention on Cardiovascular Function in CKD. CJASN 2013. 8 (9) 1494-1501.

  11. Levin A, Stevens PE, Bilous RW, Coresh J, De Francisco ALM, De Jong PE. Kidney disease: Improving global outcomes (KDIGO) CKD work group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney International Supplements 2013;3(1):1-150.

  12. Levey AS, Coresh J, Greene T, Steven LA, Zhang YP, Hendriksen S et al. Using Standardized Serum Creatinine Values in the Modification of Diet in Renal Di;sease Study Equation for Estimating Glomerular Filtration Rate. Ann Int Med 2006;145(4):247-254.

  13. Matsushita K, Selvin E, Bash LD, Astor BC, Coresh J. Risk Implications of the New CKD Epidemiology Collaboration (CKD- EPI) Equation Compared With the MDRD Study Equation for Estimated GFR: The Atherosclerosis Risk in Communities (ARIC) Study. Am J Kid Dis 2010;55(4):648-659.

  14. Hebert LA, Bay WH. On the natural tendency to progressive loss of remaining kidney function in patients with impaired renal function. Med Clin North Am. 1990;74:1011-1024

  15. Ahmed S, Jafri L, Khan AH. Evaluation of ‘CKD-EPI Pakistan’ equation for estimated glomerular filtration rate (eGFR): a comparison of eGFR prediction equations in Pakistani population. JCPSP J COLL PHYSICI 2017;27(7):414-418.

  16. Stevens PE, Levin A; Kidney Disease: Improving Global Outcomes Chronic Kidney Disease Guideline Development Work Group Members. Evaluation and management of chronic kidney disease: synopsis of the kidney disease: improving global outcomes 2012 clinical practice guideline. Ann Intern Med. 2013 Jun 4;158(11):825-30. doi: 10.7326/0003- 4819-158-11-201306040-00007.

  17. Varma PP, Raman DK, Ramakrishnan TS, Singh P, Varma A. Prevalence of early stages of chronic kidney disease in apparently healthy central government employees in India. Nep Dial Transp 2010.

  18. Singh AJ, Farag YMK, Mittal BV, Subramanian KK, Reddy SRK, Acharya VN et al. Epidemiology and risk factors of chronic kidney disease in India – results from the SEEK (Screening and Early Evaluation of Kidney Disease) study. BMC Nephrol 2013;14:114.

  19. Alsuwaida AO, Farag YM, Al Sayyari AA, Mousa D, Alhejaili F, Al-Harbi A. et al.Epidemiology of chronic kidney disease in the kingdom of saudi arabia (SEEK-saudi investigators) - a pilot study. Saudi J Kidney Dis Transpl 2010;21(6):1066–72.

  20. Chen J, Wildman RP, Gu DF, Kusek JW, Spruill M, Reynolds K. Prevalence of decreased kidney function in Chinese adults aged 35 to 74 years. Kid Int 2005;68;2837-2845.

  21. Ingsathit A, Thakkinstian A, Chaiprasert A, Sangthawan P, Gojaseni P, Kiattisunthorn K et al. Prevalence and risk factors of chronic kidney disease in the Thai adult population: Thai SEEK study. Nephrol Dial Transpl 2010;25(5);1567–1575.

  22. Zhang L, Wang F, Wang L, Wang W, Liu B, Liu J. Prevalence of chronic kidney disease in China: a cross-sectional survey. 2012;379(9818):815- 822.

  23. Ninomiya T, Yutaka K, Kubo M, Tanizaki Y, Doi Y, Obuko K. Chronic kidney disease and cardiovascular disease in a general Japanese population: The Hisayama Study. Kid Int 2005;68:228–236.

  24. Wong LY, Liew AST, Weng WT, Lim CK, Vathsala A, Tols MPHS. Projecting the Burden of Chronic Kidney Disease in a Developed Country and Its Implications on Public Health. Int Journ Nephrol 2018; Article ID 5196285.

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