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Saudi Journal of Kidney Diseases and Transplantation
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Year : 2021  |  Volume : 32  |  Issue : 6  |  Page : 1577-1585
Associations between Body Mass Index in Hemodialysis Patients and Comorbidity, Dialysis Adequacy, Blood Pressure Control, Vascular Access Type, and Hospital Admission Rate

1 College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia
2 College of Medicine; Division of Nephrology and Renal Transplantation, King Abdulaziz Medical City, Riyadh, Saudi Arabia

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Date of Web Publication27-Jul-2022


Higher body mass index (BMI) is associated with various comorbidities. In hemodialysis (HD) patients, BMI affects dialysis adequacy and blood pressure (BP) control and is associated with serious comorbidities. This is a cross-sectional observational study that took place at King Abdulaziz Medical City, Riyadh, Saudi Arabia. A total of 262 adult patients on HD for at least six months were recruited to this study. Chart review was used to retrospectively collect patients’ data. Categorical variables were compared using Chi-square test of proportions, whereas analysis of variance was used between categorical and continuous variables. P <0.05 was considered statistically significant. Only 17 (6.5%) patients were underweight, 90 (34.4%) had normal weight, 65 (24.8%) were overweight, and 90 (34.4%) were obese. Diabetes mellitus was the most common cause of chronic kidney disease. A significant relationship was found between BMI and dialysis adequacy (P = 0.004) with 54 (60%) obese patients having inadequate dialysis. The mean postdialysis systolic BP was the lowest in the obese BMI category (129.71 ± 18.38 mmHg, P = 0.037). The obese category scored least on the Charlson Comorbidity Index (CCI) reflecting lower risk of mortality than the other three BMI categories. Despite having the lowest overall rate of hospitalization in the previous 12 months, obese patients had higher rates of hospitalization from sepsis compared to the other three groups (P = 0.048). Despite having reduced dialysis adequacy, obese HD patients scored less on CCI, had better postdialysis BP, and had fewer hospital admissions in the previous 12 months compared to the other BMI groups. These findings distinctly contrast with what is seen among obese persons in the general population.

How to cite this article:
AlSahli LM, AlHinti S, AlOmar R, AlSulaimani A, Abdallah M, Al-Sayyari A. Associations between Body Mass Index in Hemodialysis Patients and Comorbidity, Dialysis Adequacy, Blood Pressure Control, Vascular Access Type, and Hospital Admission Rate. Saudi J Kidney Dis Transpl 2021;32:1577-85

How to cite this URL:
AlSahli LM, AlHinti S, AlOmar R, AlSulaimani A, Abdallah M, Al-Sayyari A. Associations between Body Mass Index in Hemodialysis Patients and Comorbidity, Dialysis Adequacy, Blood Pressure Control, Vascular Access Type, and Hospital Admission Rate. Saudi J Kidney Dis Transpl [serial online] 2021 [cited 2023 Feb 2];32:1577-85. Available from: https://www.sjkdt.org/text.asp?2021/32/6/1577/352418

   Introduction Top

The number of patients undergoing dialysis worldwide has reached 2.62 million in 2010 and is expected to double by 2030.[1] There is a total of 19,659 dialysis patients in Saudi Arabia. The majority of these patients are on hemodialysis (HD), whereas only 1389 are being treated by peritoneal dialysis.[2]

Obesity, a body mass index (BMI) of more than 30 kg/m2, is a worldwide health problem with a prevalence of 42.4%.[3] This problem has increased significantly in the last few decades with over 600 million obese individuals according to the World Health Organization in 2020[4] Saudi Arabia is one of the countries in which obesity is highly prevalent due to lifestyle rather than biological factors.[5] A cross-sectional study on obesity in Riyadh, Saudi Arabia, showed that 82% of participants are overweight or obese.[6]

Obesity is positively correlated with the development of various comorbid conditions including hyperglycemia and cardiovascular complications.[7] A meta-analysis showed that obesity in HD patients is associated with lower all-cause and cardiovascular mortality, whereas underweight patients had a relatively higher risk of mortality.[8] Among the general population, blood pressure (BP) is directly proportional to BMI, with BMI >25 kg/m2 resulting in higher BP levels.[9],[10] However, studies aimed at examining the relationship between BMI and BP in HD patients yielded contradicting findings. Some studies showed an association between increased BMI and elevated BP, whereas other studies showed what is known as the “paradoxical effect” in which an increased BMI is inversely associated with BP levels.[11]

The aim of this study is to evaluate the relationship between BMI in HD patients and comorbidity, dialysis adequacy, BP control, vascular access type, and hospital admission rates.

   Methods Top

This study is a cross-sectional observational study conducted at King Abdulaziz Medical City (KAMC), Riyadh, Saudi Arabia. KAMC, established in May 1983, is one of the tertiary hospitals in Riyadh that offers a wide array of services for patients and is known for its huge capacity for HD patients. The study specifically took place at KAMC dialysis center in the nephrology and renal transplantation division of the department of medicine. This center has 42 dialysis stations providing four dialysis shifts per day/six times a week for approximately 300 patients. All adult (≥18 years) HD patients of both genders registered at the BESTCare system at KAMC who have been on dialysis for at least six months were included in our study. Patients on dialysis for less than six months were excluded from this study to ensure stabilization of the patient and exclusion of acute illness in the patients. Nonprobable consecutive sampling was the sampling method used for this study. Using Raosoft Sample Calculator, the optimal sample size was 170 assuming that the margin of error is 5%, confidence level 95%, and a population of 304. However, all patients on HD at KAMC who fulfill the inclusion criteria were part of this study (approximately 300 patients).

Patients’ data accessed through BESTCare system were collected by chart review method using a special data collection form. Data were first entered into an electronic form and then transferred to an Excel sheet using Microsoft Excel. After cleaning the data and excluding participants who failed to meet our inclusion criteria, the data were coded to begin the analysis process. Our independent variable is BMI. Patients were categorized into four groups according to their BMI. Patients with BMI of <18.5 kg/m2 were considered underweight, patients with BMI between 18.5 kg/m2 and 24.9 kg/m2 were considered normal weight, patients with BMI between 25.0 kg/m2 and 29.9 kg/m2 were considered overweight, and patients with BMI >30 kg/m2 were considered obese. This categorization was based on the “Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults”.[12] The dependent variables in this study are BP, comorbidity, dialysis adequacy, hospitalization, and vascular access type.

BP was taken as a continuous variable and was assessed using mean and standard deviation (SD). The Charlson Comorbidity Index (CCI) was used to assess the patients’ comorbid conditions and was described using mean and SD. Kt/v measurement was used to assess dialysis adequacy. Patients were divided into two groups; a Kt/v of less than or equal to 1.2 reflects inadequate HD, whereas a Kt/v value of more than 1.2 indicates adequate HD. Patients were divided into three groups based on vascular access type (permanent catheter, arteriovenous graft, and native arteriovenous fistula).

Patients were grouped into either hospitalized or not hospitalized in the previous 12 months. The hospital admission rate (for those who were hospitalized) was described as mean ± SD. In addition, the relationship between BMI and the cause of hospitalization was studied. Dialysis-related biochemical markers were represented as mean ± SD.

   Statistical Analysis Top

The IBM SPSS Statistics version 23.0 (IBM Corp., Armonk, NY, USA) was used for analysis. The continuous variables were described using mean and SD, whereas categorical variables were reported using percentages and frequencies. Analysis of variance was the test of choice between the independent categorical variable (BMI) and the dependent continuous variable (BP) to compare the means of BP of each of the four BMI categories we have. Chi-square test of proportions was used to compare categorical variables with BMI. A P-value of less than 0.05 was considered statistically significant in this study. The study was ethically approved by the Institutional Review Board (IRB) of King Abdullah International Medical Research Center on the July 23, 2020, with Memo Ref. No. IRBC/1246/20.

   Results Top

Sociodemographic profile of participants and their relevant medical history

Among 304 patients undergoing HD at KAMC dialysis center, 42 patients failed to meet the inclusion criteria and were excluded. This left 262 patients available for the study, 122 (46.6%) were male, and the mean age among all the patients was 63.71 ± 17.81. Seventeen patients (6.5%) were underweight, 90 (34.4%) had normal weight, 65 (24.8%) were overweight, and 90 (34.4%) were obese. One hundred and seventy-seven (67.6%) were on antihypertensive therapy, 60 (22.9%) had a history of stroke, and 156 (59.5%) had a history of cardiovascular disease. The mean CCI score was 6.76 ± 2.76.

The most common cause of chronic kidney disease (CKD) was diabetes mellitus [Figure 1]. One hundred and sixty (61.1%) patients were on HD, 94 (35.9%) on hemodiafiltration, and only eight (3.1%) were undergoing sustained low-efficiency dialysis. The distribution of the vascular access types was 70 (26.7%), 25 (9.5%), and 167 (63.7%) for arteriovenous fistula, arteriovenous graft, and line (permcath), respectively. One hundred and forty-two (54.2%) had adequate dialysis, while 120 (45.8%) had inadequate dialysis. [Table 1] presents the dialysis profile of the patients, the means of BP readings, and biochemical markers related to dialysis.
Table 1. Dialysis profile of the patients (n = 262).
SD: Standard deviation, SBP: Systolic blood pressure, DBP: Diastolic blood pressure.

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Figure 1. Causes of chronic kidney disease

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Regarding hospitalization, 178 (67.9%) patients were hospitalized in the previous 12 months with a mean rate of 2.51 ± 1.76. Causes of hospitalization were as follows: six (3.4%) − cerebrovascular accident (CVA), 24 (13.5%) − cardiovascular disease, 36 (20.2%) - chest infection, 35 (19.7%) - vascular access infection, 33 (18.5%) due to vascular access complication excluding vascular access infection, 51 (28.7%) due to sepsis, and 122 (68.5%) were hospitalized due to other reasons.

A significant association was found between BMI and history of stroke (P = 0.002). Thirty (33.3%) patients of normal weight had a history of stroke compared to only nine (10%) patients in the obese BMI category. Moreover, a history of cardiovascular disease was highest among the underweight and normal BMI categories, 11 (64.7%) and 61 (67.8%), respectively.

BMI was also significantly associated with dialysis adequacy (P = 0.004). Fifty-four (60%) obese patients had inadequate dialysis (Kt/v is ≤1.2); however, when assessing comorbidity, they had the lowest CCI score with a mean of 6.32 ± 2.44. The highest CCI score was found among normal-weight individuals with a mean of 7.38 ± 3.04, as presented in [Table 2]. A significant difference in the postdialysis systolic BP (SBP) was observed across different BMI classes (P = 0.037). Tukey’s posthoc test revealed that patients with normal BMI had a significantly higher postdialysis SBP compared to obese patients. The postdialysis SBP was found to be the lowest in the obese BMI category, as shown in [Table 2]. No significant relationship was found between BMI and any of the following: predialysis SBP, predialysis diastolic BP (DBP), post dialysis DBP, difference in SBP pre- and postdialysis, and difference in DBP pre- and postdialysis of three consecutive weekend sessions in the month of February 2021. Regarding dialysis-related biochemical markers, no significant difference was found among different BMI categories, as presented in [Table 2].
Table 2. Body mass index relationship with various continuous variables
*Significant at level 0.05. SBP: Systolic blood pressure, DBP: Diastolic blood pressure.

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[Table 3] shows that 10 (58.8%) underweight patients and 68 (75.6%) normal-weight patients were hospitalized in the previous 12 months (P = 0.263). In addition, the rate of hospitalization was highest in the underweight BMI category with a mean of 2.90 ± 1 and lowest in the obese category with a mean of 2.2 ± 1.35 (P = 0.135). A significant association was seen between hospitalization due to sepsis and BMI classes (P = 0.048). Normal-weight and obese patients were noted to have higher rate of hospitalization due to sepsis compared to other BMI classes. Only eight (13.6%) out of 59 obese patients were hospitalized in the previous 12 months due to vascular access infection compared to 17 (25%) out of 68 normal-weight patients. For hospitalization due to vascular access complications other than infection, only seven (11.9%) patients from the obese category were hospitalized compared to 14 (20.6%) from the normal-weight category.
Table 3. Body mass index relationship with hospitalization.
*Significant at level 0.05.

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   Discussion Top

A direct linear relationship exists between BMI and both SBP and DBP in the general population.[13] However, these two variables show an inverse relationship in chronic HD patients. Our study shows a significant relationship between BMI and postdialysis SBP (P = 0.037). The mean of postdialysis SBP in the obese group was lower compared to the other BMI categories. A cross-sectional study conducted by Bawazir et al[11] also demonstrated this reverse epidemiology, in which a significant inverse relationship existed between postdialysis SBP (P = 0.049) and DBP (P = 0.020) with patients’ BMI. The mean of postdialysis SBP and postdialysis DBP was reported to be the lowest in the obese category (138.6 ± 26.8 mm Hg and 78.4. ± 15 mm Hg, respectively) and highest in normal-weight individuals (146.4 ± 28.6 mm Hg and 82.6 ± 14.2 mm Hg, respectively). Agarwal[14] also reported a similar paradoxical association between BMI and BP in the HD population. Both high BP and poor BP control were reported among low-BMI patients.[14] A possible explanation for this decrease in postdialysis BP of obese HD patients could be their ability to effectively isolate excess fluid to the extracellular space.[14] This inverse epidemiology was also reported by Losito et al.[15] Their study showed that patients who developed postdialysis hypertension (HTN) had lower body weight compared to those who did not. A possible explanation for this might be the reduced sodium loss in low-weight individuals using a 139 mEq/L sodium concentration dialysate. This can lead to a diffusive influx of the sodium from the dialysate, particularly in patients with low sodium concentration before the dialysis. As a result of this sodium builds up, the volume of extracellular fluid increases.[15]

Patients with CKD have a higher risk of multiple comorbidities which increase their rate of hospitalization. Our results show that underweight patients have the highest annual rate of hospitalization among all BMI groups with a mean rate of 2.90 ± 1. Conversely, overweight and obese patients were less likely to be hospitalized with a mean rate of hospitalization of 2.29 ± 1.86 and 2.2 ± 1.35 for overweight and obese BMI categories, respectively. The results of our study were consistent with the findings reported by Carrero et al[16] which concluded that underweight patients and patients that lost weight in a short period of time were associated with higher hospitalization rates. This is likely due to the clinical instability and poor nutritional status of these patients. A study by Johansen et al[17] also shows that hospitalization risk and mortality rate were lower among the high-BMI category. This survival advantage, referred to as the “obesity-survival paradox,” has been previously reported in literature. Multiple studies reported that overweight and obese HD patients had higher survival rates than normal and underweight HD patients.[8],[18] A study conducted by Locham et al[19] revealed that the incidence of sepsis among HD patients was 12.66 per 100 persons per year. The study also showed that 40.7% of chronic HD patients who developed sepsis were suffering from obesity alongside a high number of various comorbidities.[19] The results of our study showed a significant association between hospitalization due to sepsis and different BMI classes (P = 0.048). Interestingly, in our study, there were a higher number of hospital admissions due to sepsis not only among the obese but also normal-weight patients.[19]

Among the general population, obesity brings about devastating health problems and comorbidities such as HTN, atherosclerosis, as well as cerebrovascular events.[20] Lavie et al[7] stated that when the BMI increases by one unit, the risk for ischemic stroke and hemorrhagic stroke rises by 4% and 6%, respectively. In regard to chronic HD patients, a limited number of studies investigated the presence of a relationship between patients’ BMI and the development of chronic illnesses. Bossola et al[21] evaluated the presence of comorbidities among HD patients through the use of CCI. The CCI score was found to be significantly higher among obese compared to overweight and normal-weight individuals (P = 0.02). These findings are consistent with the findings of other studies conducted on the general population.[22],[23] Interestingly, our study shows conflicting results. Although not statistically significant, obese patients showed to have less comorbidities compared to patients in the other BMI groups when assessed using CCI. Bossola et al[21] did not include the underweight category in the study analysis due to the insufficient number of patients. Thus, it was impossible to compare the mean CCI scores of the underweight patients in our study with that of Bossola et al. In addition, they reported that the prevalence of HTN as well as coronary and cerebrovascular diseases was significantly higher among overweight and obese HD individuals. In contrast, our study revealed that hospitalization due to CVAs was the least in the overweight and obese BMI categories, 0 (0%) and one (1.7%), respectively. Furthermore, a history of previous CVA was the least in the obese category and the highest in the normal BMI category, nine (10%) and 30 (33.3%), respectively. Further studies are needed to evaluate and possibly explain these contraindicating findings.

There is insufficient literature on the relationship between BMI and dialysis adequacy in chronic HD patients. Hong and Lee[24] examined dialysis adequacy using spKt/v in different BMI categories and reported that high BMI was associated with lower Kt/v. In addition, a study by Salahudeen et al[25] showed a negative correlation (r = –0.3, P <0.0001) between BMI and Kt/v. Underweight and normal-weight individuals had higher Kt/v values compared to overweight individuals. Furthermore, the number of patients with inadequate dialysis was higher in the overweight category. In agreement with Salahudeen et al, the highest percentage of inadequate dialysis in our study was among the obese category. Both Hong and Salahudeen et al examined the relationship between BMI, dialysis adequacy, and mortality rates.[24],[25] Hong found that at all Kt/v levels, patients with low BMI had a higher mortality risk. Similarly, Salahudeen et al reported that the highest mortality rate was among underweight individuals.[25]

Our study has some limitations that need to be addressed. First, the study design did not allow us to determine the effect of BMI and dialysis adequacy on the survival of chronic HD patients. The interesting observation of the survival advantage of higher BMI patients despite low Kt/v values was intriguing. Therefore, a follow-up of our participants in the future might help us reach a better understanding of this obesity-survival paradox and confirm whether this phenomenon also exists in Saudi Arabia. Second, the distribution of our participants among the four BMI categories may have affected our findings since the underweight category had only 17 patients falling under it.


The present study shows that dialysis adequacy, BP control, comorbidities, and hospitalization rate of HD patients are influenced by their BMI. Despite having inadequate dialysis, obese HD patients scored less on CCI, had better postdialysis BP, and showed to have less hospital admissions in the previous 12 months compared to the other BMI groups. These findings distinctly contrast those seen among the general population. This inverse epidemiology is not well established in Saudi Arabia, and further research is necessary to confirm these observations. Moreover, additional investigations are needed to determine other patient-related factors that might significantly affect dialysis outcome, as BMI might be only one of multiple factors that are yet to be established. Maximizing the research efforts regarding the treatment and its influencing factors can help educate patients and their caregivers to start implementing lifestyle modifications that might improve treatment outcomes.

Conflict of interest: None declared.

Ms. Lama M. AlSahli and Ms. Sara AlHinti contributed equally in the preparation of the manuscript.

   References Top

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Dialysis in the Kingdom of Saudi Arabia. Saudi J Kidney Dis Transpl 2018;29:1012-20.  Back to cited text no. 2
Hales C, Carroll M, Fryar C, Ogden C. Prevalence of obesity and severe obesity among adults: United States: 2017–2018. NCHS Data Brief 2020;360:1-8.  Back to cited text no. 3
Obesity and Overweight; 2020. Available from: http://Who.int. [Last accessed on 2020 Nov 14].  Back to cited text no. 4
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Abdullah Bawazir LA, Sianipar W, Buntaran S, Kekalih A. The relationship between body mass index and blood pressure in patients undergoing chronic hemodialysis: A reverse epidemiology in Jakarta, Indonesia. Saudi J Kidney Dis Transpl 2020;31:62-9.  Back to cited text no. 11
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Agarwal R. Body mass index-mortality paradox in hemodialysis: Can it be explained by blood pressure? Hypertension 2011;58: 1014-20.  Back to cited text no. 14
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Carrero JJ, Cabezas-Rodríguez I, Qureshi AR, et al. Risk of hospitalization associated with body mass index and weight changes among prevalent haemodialysis patients. Nefrologia (Engl Ed) 2018;38:520-7.  Back to cited text no. 16
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Locham S, Naazie I, Canner J, Siracuse J, Al-Nouri O, Malas M. Incidence and risk factors of sepsis in hemodialysis patients in the United States. J Vasc Surg 2021;73:1016-21.e3.  Back to cited text no. 19
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Bossola M, Giungi S, Luciani G, Tazza L. Body mass index, comorbid conditions and quality of life in hemodialysis patients. J Nephrol 2009;22:508-14.  Back to cited text no. 21
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Correspondence Address:
Lama M. AlSahli
College of Medicine,King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
Saudi Arabia
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/1319-2442.352418

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  [Table 1], [Table 2], [Table 3]


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