Risk Factors of Chronic Kidney Disease Among Patients Attending at Dessie Comprehensive Specialized Hospital, Dessie, Amhara Region, Northeastern Ethiopia: Unmatched Case–Control Study

Abbreviations

CKD: Chronic Kidney Disease

CKD: Epi - Chronic Kidney Disease Epidemiology Collaboration

CVDs: Cardiovascular Disease,

DM: Diabetic Mellitus

DCSH: Dessie Comprehensive Specialized Hospital

ESRD: End Stage Renal Disease

GFR: Glomerular Filtration Rate

HIV: Human Immune Deficiency Virus

HTN: Hypertension

KDOQI: Kidney Foundation Disease Outcomes Quality Initiative

LMIC: Low- and Middle-Income Countries

NGOs: Non-Governmental Organizations

NCDs: Non-Communicable Disease

OPD: Outpatient Department

OTC: Over-counter Medications

RRT: Renal Replacement Therapy

SDG: Sustainable Development Goal

UTI: Urinary Tract Infections

Introduction

Background

Chronic kidney disease is defined as structural and functional kidney abnormalities or Glomerular Filtration Rate <60 ml/ min/1.73m2 for more than 3 months [1]. When these structural changes, it become conspicuous and result in a decrease in the kidney's ability to process wastes in the blood and perform other functions. During early stages, patients may present with average or slightly decreased Glomerular Filtration Rate and albuminuria [2-6]. According to Kidney Foundation Disease Outcomes Quality Initiative (KDOQI) Chronic kidney disease is divided into five stages from mild kidney dysfunction to complete failure [7]. Generally, a person with stage 3 or 4 of chronic kidney disease (CKD) is considered to have moderate to severe kidney damage. Stage 3 is broken up into two levels of kidney damage: 3A) a level of Glomerular Filtration Rate (GFR) between 45 to 59 ml/min/1.73 m2, and 3B) a level of GFR between 30 and 44 ml/min/1.73 m2. In addition, GFR for stage 4 is 15–29 ml/min/1.73 m2 [7,8]. Later, it leads to end-stage renal disease. Once the kidneys are starting to fail, whichever of symptoms like itchy skin, vomiting, nausea, not feeling hungry, too much or inadequate urine, trouble catching breath and trouble sleeping, edema of feet and ankles, and muscle cramps will be manifested [9].

A diagnosis of CKD is defined as the presence of decreased GFR below 60 mL/min per 1.73m2, or GFR above 60 mL/min per 1.73 m2, but with markers of renal damage, as determined by the Chronic Kidney Disease Epidemiology Collaboration (CKD-Epi) equation and at least one of the following: 1) Contracted kidneys, hypo-echoic kidneys or loss of corticomedullary differentiation on renal imaging; 2) Serum phosphate levels above 1.4mmol/l; 3) Serum calcium level below 2.2mmol/l; 4) History of kidney transplantation; 5) History of documented kidney dysfunction for more than 3 months; 6) Anemia of chronic disease (normochromic, normocytic, hyperproliferative picture), with a hemoglobin level of <10/dl [10,11].

Worldwide, the overall prevalence of CKD stages (1-5) ranges from 4.6% up to 15.8% in the general population [12]. The annual incidence rate is reached 8% [13]. Kidney disease is the ninth leading cause of death in the United States [14]. A meta-analysis report in Mexico revealed that between 1990 and 2017, the global standardized mortality rate increased by 41.5%, jumping from 11.4 to 16.1 deaths per 100,000 inhabitants [15]. A meta-analysis report in Africa revealed that of all the chronic non-communicable diseases, CKD has had one of the most rapid recent increases in Africa and its prevalence ranges from 6.1% up to 16% [16]. The burden of CKD has been increasing in sub-Saharan Africa, the overall prevalence is significantly higher compared to North Africa for CKD stages 1–5 [16]. Nearly a quarter (13.2%) of the sub-Saharan population has CKD [17]. Though the problem is preventable, the prevalence of CKD in our country Ethiopia has been increasing in the last few years following an increasing prevalence of diabetes, cardiovascular disease, and hypertension, and its prevalence is estimated to be 12.2% [18].

Prior researchers confirmed that age, sex, family history of kidney disease, primary kidney disease, urinary tract infections, cardiovascular disease, hypertension, diabetes mellitus, nephrotoxins (non-steroidal anti-inflammatory drugs, antibiotics), the consumption of energy drinks, drug misuse and adulteration of chemical substances into herbal medicines are Statically significant associated factors of CKD [14,16,19-22]. Nevertheless, in a study of CKD determinants like chat chewing, and HIV AIDS status, sources of water use-related variables were not well studied.

To address the CKD problem of Ethiopia sustained efforts from nongovernmental organizations (NGOs), governmental agencies, the pharmaceutical industry, and medical training programs are needed [23]. Even though there are shreds of evidence suggesting the high burden of CKD in Ethiopia it is concealed behind statistics [24]. Moreover, the existing data are hampered by the poor quality that limits inferences. Studies about CKD are almost non-existent and its determinants remain unknown Further, with the existence of low or no dialysis/kidney replacement infrastructure, strong evidence-based prevention interventions are recommended.

Hence, in Ethiopia prevention and early detection of CKD to slow its progression are of paramount importance. Therefore, this study aimed to identify the determinants of chronic kidney disease among patients attending Dessie's comprehensive specialized hospital.

Methods

Study Setting, Design, and Period

The study was conducted in Dessie Comprehensive Specialized Hospital, Dessie town, Amhara region, Northeast Ethiopia. A Hospital-based unmatched Case-control study was conducted during the study period from May 10 to July 15, 2022.

Sample Size Determination and Sampling Procedure

Sample Size Determination

The sample size was calculated by considering the following assumptions; 95% confidence level 80% power, 34.3% proportion of hypertension in a previous study, adjusted odds ratio of 2.39, 10% non-response rate, and 2:1 control to case ratio [25]. Using unmatched case-control in Epi info version 7.2.2.6 software Stat Calc. Based on the above assumptions the estimated optimal sample size used for this study was 234 (156 controls and 78 cases).

Sampling Technique and Procedure

All cases with confirmed CKD disease by urologist and full-filling case selection criteria as indicated from their medical record and at the time of data collection were included in the study until the total sample size was obtained. Primarily, patients with CKD in the hospital were small in number, thus all the available cases were considered to be included in the study. Controls were selected by a systematic random sampling method to get the required sample of controls. The average estimated total urological cases without including CKD in the total study period using average weekly urological patient flows of May 2022 was 333 and Kth interval from N/n = 333/156=2.13~ 2. Controls were selected by every 2 intervals and the first study subject of control was determined daily and selected by lottery method using the medical record number of patients. On a daily base, control was selected proportionally for cases based on control to to-case ratio until the required number of cases was obtained.

Study Variables

Dependent Variable

• Chronic Kidney Diseases (Yes/No)

Independent variable

• Socio-Demographic Characters: like age of patients, sex, place of residence, educational level, occupation, and income

• Comorbidities: like diabetes mellitus, hypertension, CVD, HIV/ AIDS, kidney stones, recurrent urinary tract infection, family history of chronic kidney diseases, history of burns, anemia

• Behavioral and Lifestyle Factors: Smoking, Alcohol drinking Chat chewing, physical exercise, consumption of unhealthy drinks and diet, and Consumption of over-the-counter medications.

Operational Definitions

• Chronic Kidney Disease (CKD): is defined as structural/ functional abnormalities of the kidney or decreased GFR <60 ml/ min/1.73m2 for more than 3 months [17]. According to the Kidney Foundation Disease Outcomes Quality Initiative (KDOQI), CKD is divided into five stages of kidney damage, from mild kidney dysfunction to complete failure [7]. Generally, a person with stage 1(GFR > 90 ml/min/1.73 m2) is considered to be normal, stage 2 (GFR between 60-89 ml/min/1.73 m2) which is mild, additionally CKD is considered as having moderate to severe kidney damage. Stage 3 is further broken up into two levels of kidney damage: 3A) a level of GFR between 45 to 59 ml/min/1.73 m2, and 3B) a level of GFR between 30 and 44 ml/min/1.73 m2. In addition, GFR for stage 4 is 15–29 ml/min/1.73 m2 later, it leads to end-stage renal disease (ESRD) [7,8].

• End-Stage Renal Disease (ESRD): kidney failure is defined as a GFR<15 mL/min/1.73 m² or very high albuminuria (>300 mg albumin/24 h) [12,13]. ESRD is irreversible and fatal unless treated by dialysis or kidney transplant [3-5]. Indicating that the kidney has stopped working permanently.

• Glomerular Filtration Rate (GFR): is a measure of how well kidneys are cleaning blood-taking out extra water and waste. Specifically, it estimates how much blood passes through the glomeruli each minute [26]. It is central to the diagnosis and management of Chronic Kidney Disease and accepted as the best overall measure of kidney function. GFR can be calculated from standardized serum Creatinine and estimating equations, such as the Modification of Diet in Renal Disease (MDRD), Study equation CKD-EPI, or the Cockcroft-Gault formula [27]. The severity of kidney disease can be classified into five stages according to the level of GFR which is given as: According to Kidney Foundation Disease Outcomes Quality Initiative (KDOQI).

• The CKD-EPI: equation, expressed as a single equation, is: GFR = 141 * min(Scr/κ,1)α * max(Scr/κ, 1)-1.209 * 0.993Age * 1.018 [if female] * 1.159 [if black] Scr is serum creatinine (mg/ dL), κ is 0.7 for females and 0.9 for males, α is -0.329 for females and -0.411 for males, min indicates the minimum of Scr/κ or 1, and max indicates the maximum of Scr/κ or 1[10].

• Diabetic Mellitus: defined as random blood sager >200mg/dl or FBS> 126mg/dl and/or self-reported on anti-hyperglycemic medication [28].

• Hypertension; defined as a systolic (SBP) ≥140 mmHg and/or diastolic blood pressure of (DBP) ≥90 mmHg or self-reported on anti-hypertension drugs [28].

• Renal Replacement Therapy: a therapy that replaces the normal blood-filtering functions of kidneys are used when the kidneys are not working well [29].

• Hemodialysis: a type of treatment that filters the blood through a machine. It Removes harmful waste and extra fluids the body no longer needs. Also, hemodialysis helps control blood pressure, and balance potassium, sodium, calcium, and bicarbonate [30].

• Over-The-Counter Medicine (OTC): defined as nonprescription medicine, that can buy without a prescription including NSAID and some other commonly used drugs and herbal medications to treat aches and pains [31].

• Ever Chat Chewer: defined as a respondent who chewed chat during his lifetime [32].

• Sufficient Salt Intake: individuals who take no more than 6g of salt a day (2.4g sodium) which is equivalent to one teaspoon [33].

• Sufficient Fat Intake: individuals who take up to 35% of the calories from fat that is equivalent to 97 grams in a 2500-calorie diet [33].

• Sufficient Sugar Intake: an individual who consumes no more than 150 discretionary calories of sugar is equivalent to 38 g or 9 teaspoons (tsp) of sugar per day for men and no more than 100 discretionary calories of sugar equivalent to 25 g or 6 tsp of sugar per day for women [34].

• Significant Alcohol Intake: individuals who take more than 2 standard drinks of alcohol for males and more than 1 per day for females. For E.g. 1 standard drink standard bottle of regular beer and the net alcohol content of a standard drink is approximately 10g of ethanol [35].

• Sufficient Physical Exercise: Adults doing at least 150–300 min of moderate-intensity aerobic physical activity per week [33].

• Ever Smoker: A person who has ever been a cigarette smoker or cigar smoker [34].

• Underground Water: These are sources of water found beneath the land surface it including springs and wells [36].

Data Collection Tools and Procedures

Data were collected using a semi-structured interviewer- administered questionnaire with support of medical records review to address all important variables using their medical record numbers when they return to the outpatient department for a checkup. The questionnaire was adapted from different literature and guidelines developed for a similar purpose by a different author.

Two data collectors and one supervisor were recruited and trained on how to collect data and check the completeness of data and training was given by the principal investigator for one day. There was continuous supervision by the principal investigator and trained supervisor.

Data Quality Control

The questionnaire was originally prepared in English and it was translated to local language (Amharic) for the purpose of data collection and then translated back to English by language experts to ensure its correctness and consistency. Two weeks before the commencement of the study, the semi-structured interviewer- administered questionnaires were pre-tested among 5% (4 cases and 8 controls) of a total of 12 samples in Kombolcha General Hospital by their local languages to prevent information leakage for the purpose of checking whether questions are clear or not, then after necessary corrections were done for unclear questions based on the pretesting findings. Internal consistency of the data was checked using Cronbach’s alpha with a value of 0.75.

Data Management and Statistical Analysis

After the data were checked for completeness and consistency, coded and entered into Epi data version 4.6 software. Finally, the data were exported to and analyzed by STATA version 14 software. Descriptive statistics like frequencies and percentages were calculated to see the distribution of the variable.

To find out the risk factors of CKD, first bivariable logistic regression was conducted and variables having a P-value of < 0.2 were entered in multivariable logistic regression analysis to control the possible confounders. Finally, variables in the multivariable logistic regression analysis having a P-value of <0.05 and the corresponding AOR with 95% confidence level was declared as a statistically significantly associated variables with CKD. To check co-linearity between risk factors, tolerance and variance inflation factors (VIF) were used. The Hosmer–Lemeshow test for the model was checked to assess whether the necessary assumptions for the application of multiple logistic regression are fulfilled or not.

Ethical Consideration

Ethical clearance was obtained from the Institutional Research Ethical Review Committee (IRERC) of Wollo University, College of Medicine and Health Sciences ethically approved the study with a letter reference number (CMHS/345/2022 on the date of 23/04/20222). The procedure and purposes of the study were explained to Dessie's comprehensive specialized hospital. A letter of support was then obtained from Dessie Comprehensive Specialized Hospital with a letter reference number (DCSH- 2/742/2022 on the date of 03/05/2022). Then permission and support letters were written to the medical ward department. Clients were asked for their consent verbally to confirm their willingness to participate in the study. Before enrolling any of the eligible study participants, the purpose, benefits, and confidential nature of the study were described and discussed with each participant. Confidentiality was ensured by omitting the names of the respondents from the questionnaire. Only those that consented and proved their willingness to take part in the study were enrolled in the study. The importance of medical check-ups, early detection, prompt medical management, nutrition relevance to CKD, and lifestyle modifications were provided by the data collectors during the data collection period.

Results

Socio-Demographic Characteristics

A total of 234 study participants (78 cases and 156 controls) were enrolled in the study making the response rate of 99% and 100% respectively. Of these, 26(33.33%) of the cases and 70(44.87%) of the controls were females. The mean age of cases and controls was 52(±14SD) and 47(±17SD) respectively. Twenty-six (33.33%) of the cases and 37 (23.72%) of the controls were above 60 years of age. Forty-two (53.85%) of case and 89 (57.05 %) of controls were live in rural area. Eighteen (23.08 %) of the cases and 28 (17.95 %) of the controls were unable to read and write. Four (5.13%) of the cases and 29(18.59%) of the controls had tertiary and above educational level. In regard to occupational status 37 (47.44 %) of cases and 58 (37.18%) of controls were self-employed, while 5 (6.41%) of cases and 20(12.82%) of controls were governmental workers. The mean monthly household income in ETB for cases and controls were 2588 and 3490 with standard deviations of ± 2243 and ± 2605 respectively (See Table 1 for detail).

Table 1: Socio-Demographic Characteristics of Study Participants Who were Attending Dessie Comprehensive Specialized Hos- pital, Ethiopia, 2022

Comorbidity Related Variables

Among the study participants, 65(83.33%) of cases and 49(31.41%) of controls had anemia. The mean hemoglobin level of participants among cases and controls was 10.2(±2.5SD) and 13.6(±2SD) re- spectively. The mean creatinine level of study participants among cases and controls was 3.26 and 0 .88 with a standard deviation of ± 2.1 and ±0.5 respectively. About 52 (66.67%) of cases and 44 (28.21%) of controls had hypertension. Among the participants, 25(48.08%) cases and 21(47.73%) controls had hypertension of fewer than five-year duration. Thirty-two (41.03%) of the cases and 24(15.38%) of controls had diabetes mellitus, of which 14 (43.75%) of the cases and 14(58.33%) of controls had diabetes mellitus less than five years duration. About Fifth-nine (75.64%) of cases and 73(46.79%) of controls had cardio-respiratory diseases. Forty-two (53.85%) of cases and 95(60.90%) of controls had a his- tory of burn. More than one-tenth (15.38) of cases and 26(16.67%) of controls live with HIV/AIDS. Roughly 64(82.05%) of the cases and 78(82.05%) of controls had a history of kidney stones. simi- larly, this study revealed that about twenty-five (32.05%) of cases and 32(20.51%) of controls had a family history of kidney disease (See Table 2 for details).

Table 2: Comorbidity-Related Factors of Study Participants Who were Attending at Dessie Comprehensive Specialized Hospital, Dessie, North-East of Ethiopia, 2022

Among 78 cases who participated in this study, 32(13.67%) were in stage 3B (30-44) or had a moderate decrease in glomerular fil- tration rates. About 21(8.8%) of cases were on stage 4 or had a severe decrease in GFR. Ten (4.27%) of cases were on stage 3A (45-59) or had a mild to moderate ecrease in GFR. About 15(6.4%) of cases reached the end stages of renal diseases (ESRD) or had GFR < 15 with or without dialysis (See Figure for detail).

Figure: Distribution of CKD by CKD-EPI Stage Classification

Lifestyle and Behavioral Factors

Among interviewed study participants, 26(33.33 %) of cases and 20(12.82 %) of controls had a history of cigarette smoking. About 42(53.85%) of cases and 72(46.15%) of controls had a history of chat chewing. Seventy-five (96.15%) of cases and 111(71.15 %) of controls consumed high in salt foods, whereas 74(94.87%) of cas- es and 104(66.67%) of controls consumed high in fat foods. About 37 (47.44%) of cases and 58 (37.18%) of controls had a history of alcohol drinking. About 70(89.74%) of cases and 89(57.05%) of controls used Non-steroid Anti-inflammatory drugs as a means of controlling pain. Fifty-two (66.67%) of cases and 65(41.67%) of controls consumed or used herbal drugs s as a means of medication (See Table 3 for detail).

 Table 3: Life Style and Behavioral Factors of Study Participants Who Attending Dessie Comprehensive Specialized Hospital in Dessie Town, Amhara Region, North-East of Ethiopia 2022

Factors Associated with Chronic Kidney Disease

The chi-square assumption was tested for further analysis and to determine determinants of Chronic Kidney Disease (CKD). Bi- variable and multivariable logistic regression analyses were con- ducted. In bivariable analysis variables with p-value <0.2 were selected for multivariable analysis and using average standard er- ror those variables with average standard error of 2.0 and above were not analyzed in the final model (like Educational status, salt, fat, caffeinated drinks, NSAID drug usage, and anemia) finally 14 variables from 29 variables (Sex of the participants, Age, hyper- tension status, diabetes-mellitus, cardio-respiratory diseases, …. Herbal medication usage history) were analyzed in multivariable analysis. The Hosmer–Lemeshow goodness of fit test for the final model was conducted for multiple logistic regression (p-value = 0.3595) the model was good since the p-value was >0.05 and the odds ratios were adjusted for all other variables keeping constant in the final models and Significant was declared using 95% CI with chronic kidney disease.

After keeping the other variables constant the odds of developing CKD among males was 2.54 [AOR; 2.54, 95% CI (1.125- 5.754)] times higher than females. Similarly, the odds of developing CKD were 5.33 [AOR; 5.33, 95% CI (2.107-13.489)] times higher for patients who had hypertension compared to those who had not. Furthermore, the odds of developing CKD among patients who had diabetes- mellitus was 3.64 [AOR; 3.64, 95% CI (1.530- 8.671)] times higher compared to their counterparts. Patients with kidney stones had 3.91 times the odds of developing CKD compared to those without kidney stones [AOR; 3.91, 95% CI (1.492-10.257)]. This study also confirmed that the use of underground water was a positive factor in CKD development [AOR; 2.63, 95% CI (1.108- 6.262)] (See Table 4 for details).

COR: Crude Odds Ratio; AOR: Adjusted Odds Ratio; UTI: Urinary Tract Infection; CKD: Chronic Kidney Disease; CKD EPI: Chron- ic Kidney Disease Epidemiology Collaboration; CVD: Cardiovascular Disease; GFR: Glomerular Filtration Rate; NCD, Non-Commu- nicable Disease. Note: Statistically Significant at *P<0.05, **P<0.01.

Table 4: Multivariable Binary Logistic Regression on Risk Factors of CKD Among Patients Attending Dessie Comprehensive Specialized Hospital, Dessie, Amhara Region, North-East Ethiopia, 2022

Discussion

The aim of this study was to identify risk factors of chronic kidney diseases among patients attending Dessie Comprehensive Special- ized Hospital, Dessie Town, Amhara region, Northeastern Ethio- pia, 2022.

The study found that males had higher odds of developing CKD than females did. It is consistent with other research conducted in Taiwan, Yemen, and Mexico [14,21,37]. The explanation could have something to do with testosterone's negative effects on males and estrogen's protective effects on females. Additionally, gender norms or social practices related to physical mobility may lim- it females' opportunities for different behaviors, as evidenced by the differences between male and female behavioral activity levels because males tend to be more active, mobile, and involved in var- ious behaviors like chat chewing, smoking, drinking alcohol, and involvement in war and accidents than females. Males are there- fore more likely to develop lung cancer, physical impairments, and drug addictions, which can lead to non-communicable diseases like hypertension, diabetes mellitus, and cardiovascular disease, which can then result in the development of CKD [1,38,39]. How- ever, studies conducted in Indonesia, Iran, and India showed that sex has no association with CKD [40-42]. These controversies might be due to the great variation of population by gender in the current study (66.67 % of cases and 55.13 % of controls) were males. Additionally, prior studies on the diagnosis of NCDs have focused more on men than on women [34].

In this study, those with a history of hypertension had five times the odds of developing CKD than those without. This finding is coherent with several related studies [17,19,21,40,42,43]. Mean- while, there is a cyclical relationship between hypertension and CKD. One possible explanation is that hypertension is one of the leading causes of CKD due to the negative effects that elevated blood pressure has on kidney vasculature. Uncontrolled high blood pressure causes high intra-glomerular pressure, which impairs glo- merular filtration. Damage to the glomeruli causes an increase in protein filtration, resulting in abnormally high levels of protein in the urine (microalbuminuria or proteinuria), which leads to renal vascular nephropathy, which gradually leads to a decrease in glo- merular filtration rate and allows enough time for other renal dis- eases to develop; alternatively, nephrons in the kidney are supplied by a dense network of blood vessels, and a large volume of blood flows through them; uncontrolled high blood pressure can cause arteries surrounding the kidney to narrow, weaken, or harden over time. These damaged arteries are unable to deliver enough blood to the kidney tissue, resulting in CKD [2,20,28,44,45]. As a result, hypertensive patients have a high probability of developing CKD compared to non-hypertensive patients. Nonetheless, an Indian study found no statistically significant link between hypertension and CKD [41]. This disagreement could be attributed to the small sample size (61 cases and 50 controls), study population differenc- es, and study settings.

In the current study, a history of diabetes was associated with high- er odds of developing CKD. This finding is in line with the find- ings of other related studies [14,21,28,46]. It is not surprising that individuals with diabetes have a higher risk of developing CKD because diabetes is a significant risk factor for kidney function and approximately 40% of individuals with diabetes end up with CKD [17,44]. One possible explanation could be Diabetes mellitus is a risk factor for the onset and progression of diabetes, character- ized by high blood glucose (sugar) levels. High levels of sugar in the blood cause damage to the arteries leading to the kidneys over time. Poor glycemic control leads to a variety of renal structural alterations, including the thickening of the glomerular basement membrane, which parallels the thickening of the capillary and tu- bular basement membranes. Then there will be increased peripher- al artery resistance due to vascular remodeling and increased body fluid volume associated with insulin resistance-induced hyperinsu- linemia and hyperglycemia, which will lead to complications such as diabetic nephropathy, secondary hypertension, and eventually CKD [41,47]. As a result, patients with diabetes have a high prob- ability of developing CKD compared to their counterparts. None- theless, a study conducted in Nepal revealed that diabetes has no statistically significant relationship with CKD [48]. This disagree- ment may be due to differences in the study setting, methods, and sample size.

When compared to those who did not have kidney stones, those who had kidney stones had roughly four times the odds of devel- oping CKD. This result agrees with other studies conducted in Ye- men, England, Kenya, and Ambo town [14,22,27,49]. This might be due to insufficient water intake or a lack of access to clean water services, as more than half of the study participants (53.85 percent of cases and 57 percent of controls) lived in rural areas, where the primary source of water was underground water, as well as living in hot climates and eating foods high in protein, salt, and sugar. These conditions may impair renal function. As a result, patients with kidney stones have a high probability of renal function im- pairment as it likely involves multiple different pathways [15,41]. Stones that obstruct urine flow have the potential to cause kidney damage. Moreover, unilateral ureteral obstruction has been shown to cause severe renal vasoconstriction, and the reduction in renal blood flow can result in significant ischemia and permanent renal parenchymal damage. As a result, nephropathy can cause inflam- mation and fibrosis in the kidneys, resulting in severe kidney dam- age [33]. Nevertheless, studies conducted in Indonesia and Taiwan revealed that kidney stone has no statistically significant associ- ation with CKD [37,40]. These discrepancies may be the result of variations in the study area, including environmental factors, dietary practices, or the study environment.

Chronic kidney diseases were positively linked to groundwater source usage compared to those who used piped water sourc- es. This finding is in line with other studies on the same subject [36,46,50,51]. The possible reason might be a large number of water quality studies to date investigated a range of harmful con- stituents in these ground waters as potential causative agents of the disease and were insufficient to ensure the microbial safety of the product water, moreover, there is high demand for product water, lack of technical capacity of the local communities, poor maintenance practices, and lack of rules and regulations for wa- ter treatment could lead to numerous environmental and public health problems [36,51]. As a result, the groundwater's alkalini- ty, hardness, and microbiological parameters exceeded the max- imum allowable levels (MALs) for drinking. Furthermore, the total dissolved solids (TDS) and magnesium levels exceeded the MALs. There were no significant seasonal differences in ground- water quality or chemical composition. The best examples of such contaminants are iconicity (primarily related to Ca2+, Mg2+, and Na+), some toxic heavy metals and metalloids (e.g., cadmium, lead, arsenic, and silica), agrochemical residues, organic matter, bacterial toxins, and certain viruses. As a result of the synergistic effect of these chemicals, the water becomes hard, contaminated, and nephrotoxic, and these conditions may reduce renal function, leading to chronic kidney diseases of unknown etiology (CKDU) [36,50]. Nevertheless, studies employed in Indonesia, and Taiwan revealed that sources of water have no static association with CKD [37,40]. These discrepancies might be explained by variations in the study area, study setting, and sample size.

Limitation

Since it is a facility-based study and mainly on governmental health facilities, this may overlook the whole community and those who have served in private health facilities. Hence, the con- ditions might underrate or overrate the conclusion. Since the study did not use the appropriate measurement for some variables like the presence of anemia, kidney stone size, and HIV test during data collection rather than using documented information and history, this may distort the information.

Conclusion

This research was conducted to identify determinants of chronic kidney disease (CKD). Study participants, who were male, had a history of hypertension, diabetes, and kidney stones, and those who used underground water sources were prone to developing CKD. Therefore, the need for increased emphasis on screening and managing the modifiable risk factors early enough so as to forestall the development and progression of the disease, Further- more, Routine urinalysis and estimation of glomerular filtration rate (GFR) for all patients, especially those with hypertension, di- abetes, kidney stones and underground water source users, could help detect CKD at an earlier stage for a better prognosis, given that the disease's course is irreversible

Declaration

Ethics Approval and Consent to Participate

An ethical clearance letter was obtained from the ethical commit- tee of the Department of Public Health, Wollo University. Before delivering the questionnaire, written consent was obtained from every participant. No names and possible identifying issues were written on the questionnaire to ensure the data was confidential.

Authors’ Contribution

Conceptualization: Abdusellam Yimer and Bilal Mohammed

Data Curation: Abdusellam Yimer and Bilal Mohammed

Formal Analysis: Abdusellam Yimer and Bilal Mohammed

Funding Acquisition: Abdusellam Yimer, Bilal Mohammed, Wel- de Melese, Reta Dewau, Wondwosen Mebratu, Abel Endawkie, Jemal Seid, Dr. Ali Hassen

Investigation: Abdusellam Yimer, Bilal Mohammed, Welde Me- lese, Reta Dewau, Wondwosen Mebratu, Abel Endawkie, Jemal Seid, Dr. Ali Hassen

Methodology: Abdusellam Yimer and Bilal Mohammed

Project Administration: Abdusellam Yimer, Bilal Mohammed, Welde Melese, Reta Dewau, Wondwosen Mebratu, Abel Endawk- ie, Jemal Seid, Dr. Ali Hassen

Resources: Abdusellam Yimer, Bilal Mohammed, Welde Melese, Reta Dewau, Wondwosen Mebratu, Abel Endawkie, Jemal Seid, Dr. Ali Hassen

Software: Abdusellam Yimer and Bilal Mohammed

Supervision: Abdusellam Yimer, Bilal Mohammed, Welde Me- lese, Reta Dewau, Wondwosen Mebratu, Abel Endawkie, Jemal Seid, Dr. Ali Hassen

Validation: Abdusellam Yimer, Bilal Mohammed, Welde Melese, Reta Dewau, Wondwosen Mebratu, Abel Endawkie, Jemal Seid, Dr. Ali Hassen

Visualization: Abdusellam Yimer, Bilal Mohammed, Welde Me- lese, Reta Dewau, Wondwosen Mebratu, Abel Endawkie, Jemal Seid, Dr. Ali Hassen

Writing – Original Draft: Abdusellam Yimer and Bilal Moham- med

Writing – Review & Editing: Abdusellam Yimer, Bilal Moham- med, Welde Melese, Reta Dewau, Wondwosen Mebratu, Abel Endawkie, Jemal Seid, Dr. Ali Hassen. All authors approved the final draft of the manuscript.

Availability of Data and Materials

The dataset containing all the required data is found at the primary author which can be accessed with a justifiable request.

Acknowledgments

The authors would like to acknowledge the staff of Wollo Univer- sity, Dessie Comprehensive Specialized Hospital s’ staff members, study participants, and data collectors for their welcome and as- sistance. Finally, we should give our genuine appreciation to our accomplices for their best regards and encouragement during this research thesis work.

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