Relationship between hypertension during dialysis and body composition in non-overweight/overweight obese patients

Jiaoyan Chen; Xianqiong Lu; Jurong Yang; Jingrong Peng; Maodi She; Yunyan Wang

doi:10.1371/journal.pone.0333566

. 2026 Apr 21;21(4):e0333566. doi: 10.1371/journal.pone.0333566

Relationship between hypertension during dialysis and body composition in non-overweight/overweight obese patients

Jiaoyan Chen ^1,^#, Xianqiong Lu ^1,^#, Jurong Yang ¹, Jingrong Peng ¹, Maodi She ¹, Yunyan Wang ^1,^*

Editor: Diego Moriconi²

PMCID: PMC13098967 PMID: 42013093

Abstract

Body composition parameters (such as BMI and waist-to-hip ratio) have a certain predictive value for blood pressure. In patients undergoing maintenance hemodialysis (MHD), BMI can affect dialysis adequacy and blood pressure control levels, and there are differences in body composition at different BMI levels. The aim of this study was to investigate the association between hypertension during dialysis and body composition in non-overweight/overweight obese patients. A total of 248 patients undergoing maintenance hemodialysis (MHD) at this center were enrolled. Body composition was measured using an InBody bioelectrical impedance analyzer prior to dialysis. Intra-dialysis blood pressure data from the preceding three months were collected via the hemodialysis system. Patients were categorized based on their dry weight at enrollment: those with BMI < 23 kg/m² were classified as the non-overweight group, and those with BMI ≥ 23 kg/m² as the overweight/obese group. LASSO regression was employed to identify body composition variables associated with hypertension during hemodialysis. Based on LASSO regression results, multivariate linear regression and logistic regression analyses were conducted to evaluate the impact of pre-dialysis body composition on blood pressure (BP) in non-overweight and overweight/obese hemodialysis patients. The overall prevalence of hypertension was 86% (214/248), and the proportion of overweight/obese patients was 41.0% (102/248). TBW and Protein were positively correlated with hypertension in non-overweight male patients (OR (95% CI): 1.28 (0.34–1.98); OR (95% CI): 1.97 (1.51–3.33)), and BMC was negatively associated with hypertension in non-overweight male patients (OR (95% CI): 0.10 (0.01–0.70)). In overweight obese female patients, Fat was positively associated with hypertension (OR (95% CI): 1.12 (1.01–2.26)). This study identified risk factors for elevated blood pressure associated with gender and BMI in a subset of the MHD Asian population. The study also provided evidence that different body composition factors (such as total body water, protein, bone mineral content, and fat) drive hypertension risk in different MHD subgroups, rather than being determined solely by BMI.

Introduction

Hypertension is prevalent in end-stage renal disease (ESRD) patients on hemodialysis, with prevalence rates reported to be as high as 90% in patients on maintenance hemodialysis (MHD) [1,2]. Growing evidence suggests that hypertension in dialysis increases the risk of death and cardiovascular events in patients with MHD [3]. The pathogenesis of hypertension in patients with MHD is complex and manifests itself as an interaction of extracellular hypervolemia, overactive sympathetic and renin-angiotensin-aldosterone systems, vascular pathology, obesity, advanced age, and other clinical conditions [4], which also significantly increases the difficulty of managing and controlling blood pressure in MHD patients.

The number of overweight and obese patients with chronic kidney disease (CKD) is increasing. Obesity is not only a recognized risk factor for hypertension [5], it is also one of the most common causes of CKD [6]. Body mass index (BMI) affects dialysis adequacy and blood pressure control in hemodialysis (HD) patients [7]. Hsu et al [8] noted that patients who are overweight or obese have more than three times the risk of developing end-stage renal disease (ESRD) compared to patients with ideal body weight. Obesity can directly contribute to CKD as an independent risk factor [9]. The effect of obesity on CKD may involve activation of the renin-angiotensin-aldosterone system (RAAS) and the interaction of leptin, lipocalin, fetuin-A, and adipose tissue [10]. Studies have shown that increased BMI is associated with increased expression of pro-inflammatory cytokines, increased oxidative stress load, and adipocytokine imbalance in patients with MHD [11], but there is still debate about the impact of obesity on CKD progression in patients with MHD [12,13].

Body composition monitoring is an important tool to assess dry weight goals in MHD patients and to better control the occurrence of dialysis events (e.g., hypotension, headache, etc.) [14]. Body composition parameters (e.g., BMI, waist-to-hip ratio) have some predictive value for blood pressure [15]. Korhonen et al [16] showed that adult adiposity, lean body mass, and blood pressure are positively correlated and that higher muscle mass may increase the risk of cardiovascular disease. The combination of a low lean body mass index (LTI) and a high adipose tissue index (FTI) may increase the risk of cardiovascular hospitalization in patients with MHD [17]. While Tian et al [18] reported that low LTI and high FTI were associated with hypotension (IDH) in dialysis. In addition, body composition varies across BMI levels. Prunceva et al [19] reported that skeletal muscle mass (SMM) and basal metabolic rate (BMR) are also higher in those with higher BMI.

Currently, reports on the relationship between BMI and blood pressure in MHD patients are inconsistent, and research on the relationship between body composition and hypertension in MHD patients is limited. It is necessary to gain a clearer understanding of the association between body composition and hypertension in MHD patients and the value of BMI in this context, as this could provide a theoretical framework for better clinical management of hypertension in MHD patients.

Materials and methods

Participants

Participants in this study were dialysis patients from the dialysis center of a tertiary general hospital in Chongqing, and the inclusion criteria were (1) age ≥ 18 years. (2) The duration of maintenance hemodialysis was ≥ 3 months, with an average of 2–3 times per week, 3.5–4 h/session. (3) No acute intercurrent illnesses had occurred in the 2 weeks before enrollment, and their clinical condition was relatively stable. (4) Informed consent was obtained. The exclusion criteria were: (1) those who combined with severe heart valve disease, atrial fibrillation, acute myocardial infarction, severe heart failure, cerebral infarction, severe edema, and severe infection. (2) Those with mental abnormalities, cognitive disorders, and those who are unable to take care of themselves. (3) Significant changes in dry weight or poor blood pressure control within 3 months prior to enrollment. (4) History of diabetes, malignant tumors, or other comorbidities associated with poor prognosis. The study protocol was adopted and approved by the hospital ethics committee. During the screening process, a total of 66 patients were excluded due to meeting exclusion criteria, primarily including poor blood pressure control within 3 months prior to enrollment (3 cases), malignant tumors (2 cases), and a history of diabetes (61 cases).

Participants were recruited through research projects. Prior to project participation, participants signed written informed consent forms; the project was approved by the Research Ethics Committee of Chongqing Medical University Third Affiliated Hospital (No. 20240085). The recruitment period for body composition measurements spanned from August 1, 2024, to November 1, 2024. Blood pressure data were extracted from the center’s information system during the same period (August 1 to November 1, 2024), collected and recorded anonymously.

Body composition measurement

Body composition at enrollment was measured using a mobile whole-body bioelectrical impedance instrument (InBody S10). Measurements were performed approximately 30 minutes before hemodialysis by a trained dialysis nurse and a nephrologist. Measurements were made by placing electrodes on the patient’s thumbs and middle fingers of both upper limbs and to the calf side of both lower limbs while the MHD patient was in the supine position. Final measurements were collected: Total Body Water (TBW), Protein, Bone Mineral Content (BMC), Fat, Basal Metabolic Rate (BMR), Mineral, Fat Free Mass (FFM), Visceral Fat Area (VFA), Muscle Mass (SLM), Skeletal Muscle Mass (SMM), Percent Body Fat (PBF)

Blood pressure data collection and definition of hypertension

Blood pressure data for MHD patients is collected through this center’s hemodialysis information system. Each blood pressure reading is measured and recorded by two professionally trained hemodialysis nurses. We use the average blood pressure during dialysis sessions occurring within approximately three months prior to the enrollment date as the final blood pressure for MHD patients. Currently, there is uncertainty about the optimal blood pressure level and type of measurement in MHD patients. Although home and ambulatory blood pressure monitoring are superior, with home blood pressure values and ambulatory blood pressure measurements correlating more strongly with left ventricular hypertrophy as well as cardiovascular mortality than clinically measured blood pressure [20,21]. However, adherence to ambulatory and home blood pressure measurements is considered a barrier for most patients due to practical limitations [22]. Our aim was to assess safety and feasibility information for this trial to determine the optimal blood pressure value during dialysis. There is also much evidence on the predictive effect of blood pressure values in the dialysis unit [22]. The criteria for determining hypertension were based on the guidelines for the diagnosis and treatment of cardiovascular disease in patients with chronic kidney disease (dialysis) and were combined with the blood pressure judgment of patients with MHD: systolic blood pressure≥140 mmHg and/or diastolic blood pressure≥90 mmHg [23].

Definition of non-overweight/overweight obese

We applied the World Health Organization’s Asian population standard [24] and based on the dry weight of the patients at the time of enrollment, we defined the non-overweight group as having a BMI < 23 kg/m² and the overweight/obese group as having a BMI ≥ 23 kg/m².

Statistical analysis

Descriptive statistics were calculated for continuous and categorical variables. Normally distributed continuous variables were expressed as mean ± standard deviation. Quantitative variables were described as mean±standard deviation, and qualitative variables were described as ratios or proportions (%). Differences in quantitative variables between genders were analyzed using the t-test. The chi-square test was used to analyze the differences in qualitative variables between the two groups. Body composition variables associated with hypertension were screened by LASSO regression. LASSO analysis converged regression coefficients to zero through a penalizing Lambda coefficient, thereby distinguishing excluded variables with zero coefficients from selected variables with non-zero coefficients to prevent overfitting and multicollinearity. These selected variables include TBW, Protein, BMC, Fat, which are considered to be most associated with hypertension. It is possible that the potential relationship between BMI and Fat resulted in the exclusion of BMI after the increase of the penalty term. To further validate our previously set ideas, after adjusting for age, we proceeded to analyze the relationship of these selected variables with blood pressure at different levels of BMI using multivariate linear regression. The effect of selected variables on hypertension at different BMI levels was analyzed by multivariate logistic regression. P < 0.05 was statistically significant.

Result

We defined hypertension as a dichotomous dependent variable (Yes = 1, No = 0) and included 14 initial variables in the LASSO regression model for feature selection, including Total Body Water (TBW), Protein, Bone Mineral Content (BMC), Fat, Basal Metabolic Rate (BMR), Mineral, Fat Free Mass (FFM), Visceral Fat Area (VFA), Muscle Mass (SLM), Skeletal Muscle Mass (SMM), Percent Body Fat (PBF), Age, Sex, and BMI. Fig 1A, coefficients for a total of 14 metrics. The 10-fold cross-validation method was applied to the iterative analysis. Because the penalty term increased, 4 variables were retained in the model as λ approached 0.02337, including TBW, Protein, BMC, and Fat. (Fig 1B).

Fig 1 — (A)LASSO coefficients for a total of 14 indicators. (B)log(λ) and biased likelihood variance. Vertical dashed lines are plotted according to the minimum criterion and the 1 SE of the minimum criterion (the 1-SE criterion).

We characterize the selected variables associated with hypertension as described above, and in addition to this, although age was excluded due to the increase in the penalty term, we still included age because it is widely considered to be associated with blood pressure and could be a potential confounder. As shown in Table 1, a total of 248 MHD patients with hypertension were 86% (214/248), 88.7% (118/133) in men and 83.5% (96/115) in women. The prevalence of overweight obesity was 41.0% (102/248), 39.8% (53/133) in men and 42.6% (49/115) in women. SBP was higher in males than females (P < 0.05), and TBW, Protein, and BMC were higher in males than females (P < 0.05).

Table 1. Comparison of patient characteristics between male and female MHD patients.

Variables	Male (n = 133)	Female(n = 115)	P
SBP	159.6 ± 19.1	153.1 ± 20.5	0.012
DBP	84.5 ± 13.2	82.3 ± 13.1	0.385
TBW	38.46 ± 6.34	29.09 ± 4.39	<0.001
Protein	10.06 ± 1.70	7.59 ± 1.19	<0.001
BMC	3.36 ± 0.69	2.67 ± 0.47	<0.001
Fat	15.55 ± 8.62	14.83 ± 8.27	0.500
Age	57.81 ± 14.89	57.96 ± 15.05	0.937
BMI	23.72 ± 4.35	22.91 ± 4.11	0.608
Hypertension			0.230
No	15(11.2)	19(16.5)
Yes	118(88.7)	96(83.5)
Overweight andobese			0.730
No	80(60.2)	66(57.4)
Yes	53(39.8)	49(42.6)

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SBP, systolic blood pressure; DBP, diastolic blood pressure; TBW, total body water; BMC, bone mineral content; BMI, body mass index.

After adjusting for age, multiple linear regression was performed with systolic blood pressure as the dependent variable and TBW, Protein, BMC, and Fat as independent variables. In non-overweight obese male patients, TBW and Protein were positively correlated with SBP(β(SE)=0.25(0.40), P = 0.033; β(SE)=0.21(1.50), P = 0.029), and BMC was negatively correlated with SBP(β(SE)=−0.20(1.30), P = 0.048). In overweight obese female patients, Fat was positively correlated with SBP (β(SE)=0.23(1.40), P = 0.015). See Table 2 for details.

Table 2. Relationship of SBP with TBW, Protein, BMC, and Fat.

Independent variables		Beta	SE	t	P	95% CI
SBP in Male
Non-overweight obese	TBW	0.245	0.404	2.163	0.033	0.071	2.679
	Protein	0.213	1.510	1.835	0.029	0.132	5.771
	BMC	−0.197	1.300	−1.807	0.048	−6.524	1.599
	Fat	0.102	0.240	0.926	0.357	0.255	1.698
	Age	0.095	0.128	0.889	0.376	−0.140	1.968
Overweight and obese	TBW	0.104	0.572	0.651	0.518	−0.782	1.527
	Protein	0.107	1.228	0.654	0.516	−3.038	5.954
	BMC	−0.056	1.514	−0.334	0.740	−8.967	4.188
	Fat	0.010	0.367	0.068	0.946	0.715	0.765
	Age	−0.059	0.249	−0.386	0.701	−0.406	0.598
SBP in Female
Non-overweight obese	TBW	0.088	0.791	0.703	0.484	−1.022	2.135
	Protein	0.109	2.143	0.832	0.408	−3.421	8.32
	BMC	−0.046	1.349	−0.358	0.721	−8.388	7.936
	Fat	0.022	0.279	0.180	0.858	0.506	0.606
	Age	0.054	0.165	0.459	0.647	−0.253	0.505
Overweight and obese	TBW	0.123	0.675	0.624	0.536	−0.945	1.788
	Protein	0.140	2.061	0.641	0.525	−3.953	7.622
	BMC	0.009	1.462	0.046	0.964	−2.773	3.367
	Fat	0.227	1.383	1.415	0.015	0.023	4.318
	Age	−0.091	0.175	−0.579	0.566	−0.855	−0.003

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SBP, systolic blood pressure; TBW, total body water; BMC, bone mineral content.

After adjusting for age, multiple linear regression was performed with diastolic blood pressure as the dependent variable and TBW, Protein, BMC, and Fat as independent variables. As shown in Table 3, in non-overweight obese male patients, TBW was positively correlated with DBP (β(SE)=0.17 (1.27), P = 0.013) and BMC was negatively correlated with DBP (β(SE = −0.183(2.25), P = 0.034).

Table 3. Relationship of DBP with TBW, Protein, BMC, and Fat.

Independent variables		Beta		SE	t	P	95% CI
DBP in Male
Non-overweight obese	TBW	0.170	1.267	1.601	0.013	0.103	2.957
	Protein	0.063	1.044	0.548	0.585	−1.503	2.647
	BMC	−0.183	2.249	−1.725	0.034	−2.592	1.349
	Fat	0.020	0.165	0.184	0.854	−0.358	0.297
	Age	−0.271	0.087	−2.612	0.081	−3.054	0.399
Overweight and obese	TBW	0.172	0.357	1.142	0.206	0.313	1.129
	Protein	0.258	1.410	1.657	0.105	0.510	5.183
	BMC	0.189	1.276	1.262	0.214	2.474	6.739
	Fat	0.123	0.239	0.813	0.420	0.278	1.688
	Age	−0.221	0.162	−1.489	0.144	−2.386	−0.068
DBP in Female
Non-overweight obese	TBW	0.138	0.479	1.176	0.244	−0.392	1.519
	Protein	0.220	1.670	1.905	0.131	−0.149	6.511
	BMC	−0.181	1.746	−1.548	0.126	−6.270	−1.669
	Fat	0.026	0.178	0.221	0.826	−0.315	0.394
	Age	−0.320	0.101	−2.842	0.126	−3.585	0.486
Overweight and obese	TBW	0.083	0.372	0.528	0.600	−0.556	0.949
	Protein	0.089	1.985	0.405	0.687	−3.211	4.821
	BMC	−0.010	1.603	−0.062	0.951	−7.507	7.058
	Fat	0.155	0.260	0.348	0.106	−0.616	0.435
	Age	−0.043	0.121	−0.270	0.788	−0.312	0.278

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DBP, diastolic blood pressure; TBW, total body water; BMC, bone mineral content.

After adjusting for age, in binary logistic regression analysis with hypertension (Yes = 1, No = 0) as the dependent variable and TBW, Protein, BMC, and Fat as independent variables, TBW and Protein were positively associated with hypertension in non-overweight males(OR (95% CI): 1.28 (0.34–1.98), P = 0.012; OR (95% CI): 1.97 (1.51–3.33), P = 0.009), and BMC was negatively associated with hypertension in non-overweight males (OR (95% CI): 0.10 (0.01–0.70), P = 0.021). In overweight obese females, Fat was positively associated with hypertension (OR (95% CI): 1.12 (1.01–2.26), P = 0.036). Details were shown in the Fig 2.

Discussion

This study identified gender- and BMI-specific body composition predictors associated with hypertension in patients with MHD, and we found that TBW and Protein were positively associated with hypertension in non-overweight male MHD patients, and BMC was negatively associated with hypertension in non-overweight male MHD patients. Fat was positively associated with hypertension in overweight obese female MHD patients.

CKD and progressive loss of kidney function can lead to sodium and water retention in the body, which can lead to arterial hypertension [25]. Currently, volume overload is the first problem to be addressed in the dialysis management of hypertension in HD patients [26]. Extracellular fluid overload and poor fluid management underlie the development of cardiovascular complications in HD patients [27]. Over time and with repeated positive fluid imbalances, patients with HD are susceptible to the accumulation of body sodium and water, which can lead to an adverse outcome of cardiovascular events from extracellular fluid overload [28]. Optimal management of fluid and sodium imbalances in HD patients can be achieved through salt intake restriction and fluid removal, dialysis and real-time monitoring and assessment of dry weight during dialysis [29]. Yet, restoring extracellular fluid homeostasis, achieving adequate blood pressure control, and maintaining ideal hemodynamic stability in dialysis patients remains a significant challenge [30]. With the support of new diagnostic and monitoring tools such as multi-frequency Bioimpedance Spectroscopy (BIS), Artificial Intelligence algorithms, etc., we will enter a new era of proposing more precise fluid management methods to ensure optimal fluid status control.

Our study found that blood pressure (BP) in non-obese MHD male patients is also associated with body protein content, and this relationship may be linked to more severe kidney function impairment. Chronic kidney damage is known to directly lead to elevated blood pressure, particularly in end-stage renal disease (ESRD) patients undergoing hemodialysis [31]. Protein-energy wasting is common in CKD patients [32], and more severe kidney function impairment may also result in greater protein-energy wasting [33], which may provide a reasonable explanation for our findings. However, whether there is a direct underlying association between BP and body protein content requires further investigation.

Previous studies have reported an association between hypertension and bone mineral loss [34], The relationship between hypertension and bone mineral content may be through a pathophysiologic link between blood pressure regulation and calcium metabolism [35], Persistent hypercalciuria and hyperparathyroidism as pathophysiologic mechanisms of increased bone mineral loss in hypertensive patients [36]. This supports our findings to some extent. Calcium-phosphorus metabolism disorders and hypertension are prevalent in MHD patients, and mineral and bone disorders (CKD-MBD) increase the risk of adverse outcomes, including cardiovascular events, in hemodialysis (HD) patients [37], monitoring bone mineral content may aid in the therapeutic management of MHD patients. In future studies, we will further incorporate laboratory indicators such as serum calcium, serum phosphorus, and parathyroid hormone to comprehensively explore the relationship between mineral metabolism and blood pressure.

In this study, we did not find any relationship between TBW and Protein and blood pressure in overweight and obese patients, which warrants further reflection on the impact of overweight and obesity on MHD patients. Li et al [38] found a nearly threefold increased risk of cardiovascular death in peritoneal dialysis patients who were obese and had uncontrolled blood pressure compared to normal weight. Obesity and hypertension are closely related, and adiposity increases the risk of insulin resistance, hypertension, and cardiovascular disease [39]. In addition, there is a “reverse epidemiology” hypothesis regarding the relationship between body mass index (BMI) and blood pressure (BP) in HD patients, with obese dialysis patients having a longer survival time [40,41]. Hou et al [42] found that overweight/obesity played a major mediating role in the correlation between lifestyle risk factors and systolic and diastolic blood pressure, as well as being at the top of the list of modifiable risk factors for hypertension. The interaction of BMI may also have had some impact on our findings. For example, Xu et al [43] found that the relationship between heart rate and the incidence of type 2 diabetes mellitus in a rural Chinese population was particularly pronounced in non-overweight/obese participants compared to overweight and obese individuals, which was due to the interaction between heart rate and BMI. However, we only found an association between Fat and BP in overweight/obese female patients, but not in males, which may be influenced by sex differences in blood pressure hemodynamics in overweight/obese individuals [44]. The gender-specific mechanisms underlying fat distribution patterns, sex hormone levels, and insulin resistance may account for sex-related differences. Sironi [45] et al. noted that visceral fat is closely associated with hypertension, insulin resistance, and metabolic syndrome. Postmenopausal women experience increased visceral fat accumulation due to declining estrogen levels, making adipose tissue a primary driver of hypertension. In male patients of this study, the association between TBW and Protein with hypertension may reflect more severe metabolic disorders and a state of protein-energy depletion. Conversely, the role of Fat in female patients more directly highlights the core position of adipose tissue as an endocrine organ in blood pressure regulation.

It is important to note that “reverse epidemiology” primarily describes the paradoxical association between obesity and mortality, and does not imply that obesity negates the risk of hypertension. This study found that in overweight and obese female patients, body fat content was independently and positively correlated with hypertension risk. This suggests that in the dialysis population, obesity may simultaneously impact survival prognosis and blood pressure regulation through distinct pathophysiological pathways. Therefore, in clinical practice, even for patients who may derive survival benefits from a higher body mass index, identifying and managing hypertension driven by specific body composition factors—such as excessive body fat—remains a critical component of optimizing cardiovascular health management. In non-overweight men, monitoring total body water (TBW) and protein status aids in identifying hypertension risk; in overweight/obese women, controlling body fat may be more beneficial for blood pressure management. This suggests that individualized intervention strategies should be developed based on body composition rather than relying solely on BMI.

We acknowledge several limitations of this study. First, similar to other cross-sectional studies, unaccounted variables or inadequately adjusted factors may introduce confounding effects. For example, due to data limitations, we were unable to include residual renal function, blood pressure variability, ultrafiltration volume, antihypertensive medication use, and other parameters in the analysis. Given that antihypertensive medication use and blood pressure variability may influence study outcomes, we conducted a three-month follow-up of patients’ blood pressure during dialysis sessions. This extended assessment may more comprehensively reflect patients’ true dynamic blood pressure patterns, thereby mitigating the impact of medications and blood pressure fluctuations on results. Furthermore, the inclusion of total body water (TBW) provides robust indirect evidence and physiological relevance supporting the clinical significance of ultrafiltration volume. Additionally, we lack documentation regarding the menopausal status and estrogen use among female patients, factors that may influence blood pressure regulation and thus constitute potential confounders when interpreting gender-related differences. Future studies should prospectively integrate these therapeutic parameters with body composition metrics to establish a complete evidence chain linking “therapeutic interventions” to “physiological states” and ultimately to “clinical outcomes”, thereby providing a foundation for precision management. Second, this study excluded patients with diabetes to control for the disease’s strong confounding effects on blood pressure and fluid balance. However, diabetes is a significant comorbidity among patients with chronic kidney disease and those on maintenance hemodialysis, often associated with more pronounced volume overload, metabolic disturbances, and blood pressure variability. Therefore, the findings of this study apply only to non-diabetic populations. Future research should validate the relationship between body composition and hypertension in diabetic patients to provide more universally applicable clinical guidance. Finally, individual variations may influence body composition and its association with outcomes, necessitating caution when extrapolating the findings of this study.

Conclusions

We found that the relationship between body composition and BP in MHD patients differed across BMI levels and gender. In non-overweight male patients, TBW and Protein had a positive effect on BP, whereas BMC had a negative effect on hypertension. In overweight obese female patients, Fat had a positive effect on hypertension. These findings help us to obtain more useful information on hypertension management from the body composition data of MHD patients and provide some references for MHD patients during clinical treatment.

Supporting information

S1 File. Raw data.

(CSV)

pone.0333566.s001.csv^{(17.5KB, csv)}

Acknowledgments

The authors would like to thank the participants for their support and cooperation in this study and the staff of the hemodialysis center for providing guidance.

Data Availability

All relevant data are within the manuscript and its Supporting information files.

Funding Statement

This study was supported by the Chongqing Science and Health Joint Medical Research Top Project [2025MSXM108].

References

1.Agarwal R, Nissenson AR, Batlle D, Coyne DW, Trout JR, Warnock DG. Prevalence, treatment, and control of hypertension in chronic hemodialysis patients in the United States. Am J Med. 2003;115(4):291–7. doi: 10.1016/s0002-9343(03)00366-8 [DOI] [PubMed] [Google Scholar]
2.Georgianos PI, Agarwal R. Resistant hypertension in dialysis: epidemiology, diagnosis, and management. Kidney International. 2024;35(4):505–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
3.De Lima JJG, Gowdak LHW, Reusing JO Jr, David-Neto E, Bortolotto LA. Interdialytic Blood Pressure and Risk of Cardiovascular Events and Death in Hemodialysis Patients. High Blood Press Cardiovasc Prev. 2023;30(3):235–41. doi: 10.1007/s40292-023-00575-4 [DOI] [PubMed] [Google Scholar]
4.Bansal N, Artinian NT, Bakris G, Chang T, Cohen J, Flythe J, et al. Hypertension in Patients Treated With In-Center Maintenance Hemodialysis: Current Evidence and Future Opportunities: A Scientific Statement From the American Heart Association. Hypertension. 2023;80(6):e112–22. doi: 10.1161/HYP.0000000000000230 [DOI] [PubMed] [Google Scholar]
5.Seravalle G, Grassi G. Obesity and hypertension. Pharmacol Res. 2017;122:1–7. doi: 10.1016/j.phrs.2017.05.013 [DOI] [PubMed] [Google Scholar]
6.Jiang Z, Wang Y, Zhao X, Cui H, Han M, Ren X, et al. Obesity and chronic kidney disease. Am J Physiol Endocrinol Metab. 2023;324(1):E24–41. doi: 10.1152/ajpendo.00179.2022 [DOI] [PubMed] [Google Scholar]
7.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(6):1577–85. doi: 10.4103/1319-2442.352418 [DOI] [PubMed] [Google Scholar]
8.Body mass index and risk for end-stage renal disease. Am J Kidney Dis. 2006;144(1):21–8. [DOI] [PubMed] [Google Scholar]
9.Kambham N, Markowitz GS, Valeri AM, Lin J, D’Agati VD. Obesity-related glomerulopathy: an emerging epidemic. Kidney Int. 2001;59(4):1498–509. doi: 10.1046/j.1523-1755.2001.0590041498.x [DOI] [PubMed] [Google Scholar]
10.Kalaitzidis RG, Siamopoulos KC. The role of obesity in kidney disease: recent findings and potential mechanisms. Int Urol Nephrol. 2011;43(3):771–84. doi: 10.1007/s11255-011-9974-1 [DOI] [PubMed] [Google Scholar]
11.Axelsson J, Rashid Qureshi A, Suliman ME, Honda H, Pecoits-Filho R, Heimbürger O, et al. Truncal fat mass as a contributor to inflammation in end-stage renal disease. Am J Clin Nutr. 2004;80(5):1222–9. doi: 10.1093/ajcn/80.5.1222 [DOI] [PubMed] [Google Scholar]
12.Kalantar-Zadeh K, Block G, Humphreys MH, Kopple JD. Reverse epidemiology of cardiovascular risk factors in maintenance dialysis patients. Kidney Int. 2003;63(3):793–808. doi: 10.1046/j.1523-1755.2003.00803.x [DOI] [PubMed] [Google Scholar]
13.Deger SM, Ellis CD, Bian A, Shintani A, Ikizler TA, Hung AM. Obesity, diabetes and survival in maintenance hemodialysis patients. Ren Fail. 2014;36(4):546–51. doi: 10.3109/0886022X.2013.876351 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Mathilakath NC, Selvaraj J, Parameswaran S, Viswanathan S, Pillai V, Kt H. Prevalence of Overhydration in Patients on Maintenance Haemodialysis As Determined by Body Composition Monitor and Effects of Attaining Target Dry Weight. Cureus. 2022;14(9):e29509. doi: 10.7759/cureus.29509 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Dahel-Mekhancha CC, Rolland-Cachera M-F, Botton J, Karoune R, Sersar I, Yagoubi-Benatallah L, et al. Body composition and anthropometric indicators as predictors of blood pressure: a cross-sectional study conducted in young Algerian adults. Br J Nutr. 2023;129(11):1993–2000. doi: 10.1017/S0007114522002719 [DOI] [PubMed] [Google Scholar]
16.Korhonen PE, Mikkola T, Kautiainen H, Eriksson JG. Both lean and fat body mass associate with blood pressure. Eur J Intern Med. 2021;91:40–4. doi: 10.1016/j.ejim.2021.04.025 [DOI] [PubMed] [Google Scholar]
17.Tian M, Lan Q, Yuan J, He P, Yu F, Long C, et al. Low Lean Tissue Index and Muscle Strength Combined with High Fat Tissue Index Are Associated with Cardiovascular Disease-Related Hospitalisation in Patients on Haemodialysis. Cardiorenal Med. 2023;13(1):363–71. doi: 10.1159/000534399 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Tian M, Zha Y, Qie S, Lin X, Yuan J. Association of Body Composition and Intradialytic Hypotension in Hemodialysis Patients. Blood Purif. 2020;49(3):334–40. doi: 10.1159/000504245 [DOI] [PubMed] [Google Scholar]
19.Burlyaeva EA, Prunceva TA, Semenov MM, Stakhanova AA, Korotkova TN, Elizarova EV. Body composition and basal metabolic rate in overweight and obese patients. Vopr Pitan. 2022;91(5):78–86. doi: 10.33029/0042-8833-2022-91-5-78-86 [DOI] [PubMed] [Google Scholar]
20.Agarwal R, Brim NJ, Mahenthiran J, Andersen MJ, Saha C. Out-of-hemodialysis-unit blood pressure is a superior determinant of left ventricular hypertrophy. Hypertension. 2006;47(1):62–8. doi: 10.1161/01.HYP.0000196279.29758.f4 [DOI] [PubMed] [Google Scholar]
21.Agarwal R. Blood pressure and mortality among hemodialysis patients. Hypertension. 2010;55(3):762–8. doi: 10.1161/HYPERTENSIONAHA.109.144899 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Miskulin DC, Gassman J, Schrader R, Gul A, Jhamb M, Ploth DW, et al. BP in Dialysis: Results of a Pilot Study. J Am Soc Nephrol. 2018;29(1):307–16. doi: 10.1681/ASN.2017020135 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Cheung AK, Chang TI, Cushman WC, Furth SL, Hou FF, Ix JH, et al. Executive summary of the KDIGO 2021 Clinical Practice Guideline for the Management of Blood Pressure in Chronic Kidney Disease. Kidney Int. 2021;99(3):559–69. doi: 10.1016/j.kint.2020.10.026 [DOI] [PubMed] [Google Scholar]
24.Zierle-Ghosh A, Jan A. Physiology, Body Mass Index. Treasure Island (FL): StatPearls. ineligible companies. Disclosure: Arif Jan declares no relevant financial relationships with ineligible companies.: StatPearls Publishing Copyright © 2025, StatPearls Publishing LLC.; 2025. [Google Scholar]
25.Spahia N, Rroji M, Idrizi A, Spasovski G, Barbullushi M. Sodium and water dynamics in the progression of chronic kidney disease: mechanisms and clinical significance. Int Urol Nephrol. 2024;56(6):1953–63. doi: 10.1007/s11255-023-03903-8 [DOI] [PubMed] [Google Scholar]
26.Flythe JE, Chang TI, Gallagher MP, Lindley E, Madero M, Sarafidis PA, et al. Blood pressure and volume management in dialysis: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney Int. 2020;97(5):861–76. doi: 10.1016/j.kint.2020.01.046 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Weiner DE, Brunelli SM, Hunt A, Schiller B, Glassock R, Maddux FW, et al. Improving clinical outcomes among hemodialysis patients: a proposal for a “volume first” approach from the chief medical officers of US dialysis providers. Am J Kidney Dis. 2014;64(5):685–95. doi: 10.1053/j.ajkd.2014.07.003 [DOI] [PubMed] [Google Scholar]
28.Lambers Heerspink HJ, Navis G, Ritz E. Salt intake in kidney disease--a missed therapeutic opportunity? Nephrology, Dialysis, Transplantation. 2012;27(9):3435–42. [DOI] [PubMed] [Google Scholar]
29.Canaud B, Chazot C, Koomans J, Collins A. Fluid and hemodynamic management in hemodialysis patients: challenges and opportunities. J Bras Nefrol. 2019;41(4):550–9. doi: 10.1590/2175-8239-JBN-2019-0135 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Zoccali C, Mallamaci F. Mapping Progress in Reducing Cardiovascular Risk with Kidney Disease: Managing Volume Overload. Clin J Am Soc Nephrol. 2018;13(9):1432–4. doi: 10.2215/CJN.01360118 [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Georgianos PI, Agarwal R. Resistant Hypertension in Dialysis: Epidemiology, Diagnosis, and Management. J Am Soc Nephrol. 2024;35(4):505–14. doi: 10.1681/ASN.0000000000000315 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Ikizler TA, Cano NJ, Franch H, Fouque D, Himmelfarb J, Kalantar-Zadeh K, et al. Prevention and treatment of protein energy wasting in chronic kidney disease patients: a consensus statement by the International Society of Renal Nutrition and Metabolism. Kidney Int. 2013;84(6):1096–107. doi: 10.1038/ki.2013.147 [DOI] [PubMed] [Google Scholar]
33.Hanna RM, Ghobry L, Wassef O, Rhee CM, Kalantar-Zadeh K. A practical approach to nutrition, protein-energy wasting, sarcopenia, and cachexia in patients with chronic kidney disease. Blood Purif. 2020;49(1–2):202–11. [DOI] [PubMed] [Google Scholar]
34.Cappuccio FP, Meilahn E, Zmuda JM, Cauley JA. High blood pressure and bone-mineral loss in elderly white women: a prospective study. The Lancet. 1999;354(9183):971–5. doi: 10.1016/s0140-6736(99)01437-3 [DOI] [PubMed] [Google Scholar]
35.Titze J. Bone mineral content and blood pressure: What is the pathophysiologic link? Am J Hypertens. 2006;19(8):877–8. doi: 10.1016/j.amjhyper.2006.01.017 [DOI] [PubMed] [Google Scholar]
36.Afghani A, Johnson CA. Resting blood pressure and bone mineral content are inversely related in overweight and obese Hispanic women. Am J Hypertens. 2006;19(3):286–92. doi: 10.1016/j.amjhyper.2005.10.024 [DOI] [PubMed] [Google Scholar]
37.Zhu J-G, Chen J-B, Cheng B-C, Lee C-H, Long G, Chien Y-S. Association between Extreme Values of Markers of Chronic Kidney Disease: Mineral and Bone Disorder and 5-Year Mortality among Prevalent Hemodialysis Patients. Blood Purif. 2018;45(1–3):1–7. doi: 10.1159/000478972 [DOI] [PubMed] [Google Scholar]
38.Li W, Xu R, Wang Y, Shen J, Li Z, Yu X, et al. Association of body mass index and uncontrolled blood pressure with cardiovascular mortality in peritoneal dialysis patients. J Hum Hypertens. 2019;33(2):106–14. doi: 10.1038/s41371-018-0107-5 [DOI] [PubMed] [Google Scholar]
39.Fahed G, Aoun L, Bou Zerdan M, Allam S, Bou Zerdan M, Bouferraa Y. Metabolic syndrome: updates on pathophysiology and management in 2021. Int J Mol Sci. 2022;23(2). [DOI] [PMC free article] [PubMed] [Google Scholar]
40.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(1):62–9. doi: 10.4103/1319-2442.279962 [DOI] [PubMed] [Google Scholar]
41.Jialin W, Yi Z, Weijie Y. Relationship between body mass index and mortality in hemodialysis patients: a meta-analysis. Nephron Clin Pract. 2012;121(3–4):c102-11. doi: 10.1159/000345159 [DOI] [PubMed] [Google Scholar]
42.Hou Y, Yang S. Association of risk factors for high blood pressure across 46 low- and middle-income countries: A multi-country cross-sectional analysis. J Glob Health. 2024;14:04087. doi: 10.7189/jogh.14.04087 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Xu C, Zhong J, Zhu H, Hu R, Fang L, Wang M, et al. Independent and interactive associations of heart rate and body mass index or blood pressure with type 2 diabetes mellitus incidence: A prospective cohort study. J Diabetes Investig. 2019;10(4):1068–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Syme C, Shin J, Richer L, Gaudet D, Paus T, Pausova Z. Sex Differences in Blood Pressure Hemodynamics in Middle-Aged Adults With Overweight and Obesity. Hypertension. 2019;74(2):407–12. doi: 10.1161/HYPERTENSIONAHA.119.13058 [DOI] [PubMed] [Google Scholar]
45.Anna Maria S, Rosa S, Franco F, Amalia G. Ectopic fat storage, insulin resistance, and hypertension. Current Pharmaceutical Design. 2011;17(28):3074–80. [DOI] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0333566.r001

Decision Letter 0

Diego Moriconi

28 Dec 2025

Dear Dr. Wang,

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Reviewer #1: Dear authors, congratulations on the manuscript and interest in the subject of hypertension in dialysis. I have a few comments I'd like to make about the work:

1) At what point during the hemodialysis session was the blood pressure value captured for the diagnosis of arterial hypertension?

2) How many individuals were excluded from the study based on the exclusion criteria?

3) Why was LASSO regression used and not ELASTIC NET regression ?

4) What about residual renal function? We know that loss of residual renal function compromises blood volume control and can impact blood pressure, while also contributing to changes in body composition. Could the men in this study, who had a correlation between total body water and systolic blood pressure, have lower residual renal function ?

5) The authors suggested that mineral and bone metabolism disorders could partially explain the correlation between bone mass composition parameters and arterial hypertension in men. However, in this study, this is merely speculative, since hypercalciuria appears to be negligible in dialysis patients, and the lack of laboratory data on mineral metabolism variables (parathyroid hormone, calcium, and phosphorus levels) precludes any conclusions in this regard. I agree, however, that new studies evaluating these laboratory variables should be carried out.

6) The question of "reverse epidemiology" in patients receiving dialysis is quite interesting, but it links obesity and overweight to lower mortality, and does not necessarily include hypertension in this conclusion. I would like the authors to weigh in more assertively at this point, specifically in dialysis patients.

7) Diabetic patients with chronic kidney disease have higher blood pressure values and are hypervolemic. Why was the variable diabetes mellitus not considered in this study?

Reviewer #2: Thank you for the effort and work put into this study. Hypertension is highly prevalent among MHD patients and is influenced by multiple inter-related factors. To further strengthen the findings and interpretation, additional information would be helpful, such as blood pressure variability across the dialysis phases (pre-, intra- and post-haemodialysis), details of antihypertensive medications and compliant, ultrafiltration volume, and other dialysis-related parameters as mentioned. These variables are important to better justify and contextualise the associations with BIA parameters. Incorporating these, may enhance the clinical relevance of the study and provide deeper insights into how BIA findings can be applied to optimise blood pressure management in MHD patients.

Additionally, there are some inconsistencies in wording and some typographical errors which would benefit from careful revision to improve clarity and overall presentation.

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PLoS One. 2026 Apr 21;21(4):e0333566. doi: 10.1371/journal.pone.0333566.r002

Author response to Decision Letter 1

8 Jan 2026

Reviewer #1:

Dear authors, congratulations on the manuscript and interest in the subject of hypertension in dialysis. I have a few comments I'd like to make about the work:

1) At what point during the hemodialysis session was the blood pressure value captured for the diagnosis of arterial hypertension?

Response: Thanks for your valuable comments. The blood pressure data used in this study were derived from the average blood pressure recorded during dialysis sessions in the dialysis center information system, specifically the average blood pressure values from each dialysis session within the three months preceding enrollment. Blood pressure during each dialysis session was measured and recorded by two professional nurses. We did not distinguish specific time periods (pre-, intra-, or post-dialysis) but instead used the overall average value throughout the entire dialysis session as the basis for analysis. This approach partially reflects the overall blood pressure burden during the dialysis process. In subsequent studies, we may further refine the time periods to analyze blood pressure heterogeneity.

2) How many individuals were excluded from the study based on the exclusion criteria?

Response: Thanks for your valuable comments. As you have considered, to further enhance the transparency and reproducibility of the study, we have supplemented the “Materials and Methods” section with details on the number of cases excluded during the screening process and their primary reasons.

3) Why was LASSO regression used and not ELASTIC NET regression ?

Response: Thanks for your valuable comments. LASSO regression is suitable for automatic variable selection in high-dimensional data, effectively preventing overfitting. It is appropriate for this study's initial scenario with a large number of variables (14). As you considered, Elastic Net combines the advantages of LASSO and ridge regression. However, when the sample size is moderate and multicollinearity among variables is not pronounced (as in this study), LASSO already performs adequate feature selection. Therefore, LASSO regression was selected.

Response: Thanks for your valuable comments and the question you raise is indeed critical. Residual kidney function (RKF) may indeed influence a patient's volume status and blood pressure levels by affecting the efficiency of sodium and water clearance. Although this study included only end-stage renal disease patients on regular dialysis for ≥3 months (most with severely impaired or absent RKF), inter-individual variations in residual renal function may still represent a potential confounding factor. This represents one limitation of our study, which we addressed in the Discussion section. Future research plans include incorporating more direct measures of RKF (such as urea clearance or urine output) to further elucidate its role in the relationship between body composition and blood pressure.

Response: Thanks for your valuable comments and we fully agree with your perspective. The discussion regarding the association between bone mineral content and hypertension in the manuscript is indeed speculative. In future studies, we will incorporate additional laboratory indicators such as serum calcium, serum phosphorus, and parathyroid hormone to more comprehensively explore the relationship between mineral metabolism and blood pressure. We have revised the relevant discussion to ensure the rigor of our findings, as detailed at the end of the fourth paragraph in the Discussion section.

Response: Thanks for your valuable comments. In the sixth paragraph under discussion, we supplement and emphasize that: although an “inverse epidemiological” phenomenon linking obesity to mortality may exist in the dialysis population, this does not negate obesity's role as a risk factor for hypertension. Our study provides new evidence for understanding the complex relationship between obesity and hypertension in dialysis patients from the perspective of body composition analysis. It further underscores that actively managing hypertension driven by factors such as body fat remains crucial in the clinical management of hemodialysis patients, even for those who may benefit from a higher BMI in terms of survival.

7) Diabetic patients with chronic kidney disease have higher blood pressure values and are hypervolemic. Why was the variable diabetes mellitus not considered in this study?

Response: Thanks for your valuable comments. As you have noted, diabetes is a common and significant comorbidity among patients on maintenance hemodialysis, with profound effects on blood pressure, volume load, and metabolic status. During the study design phase, to more clearly examine the direct association between body composition and hypertension while avoiding strong confounding effects from diabetes and its related complications (such as autonomic neuropathy and more complex volume issues), diabetic patients were deliberately excluded. Therefore, the conclusions of this study primarily apply to the non-diabetic MHD population. We have supplemented this point in the limitations section of the “Discussion” and emphasize that future research should validate these associations in diabetic populations to provide more universally applicable clinical guidance.

Reviewer #2:

1) Thank you for the effort and work put into this study. Hypertension is highly prevalent among MHD patients and is influenced by multiple inter-related factors. To further strengthen the findings and interpretation, additional information would be helpful, such as blood pressure variability across the dialysis phases (pre-, intra- and post-haemodialysis), details of antihypertensive medications and compliant, ultrafiltration volume, and other dialysis-related parameters as mentioned. These variables are important to better justify and contextualise the associations with BIA parameters. Incorporating these, may enhance the clinical relevance of the study and provide deeper insights into how BIA findings can be applied to optimise blood pressure management in MHD patients.

Response: Thanks for your valuable comments. We fully agree that parameters such as blood pressure variability, antihypertensive medication use, and ultrafiltration volume are crucial for gaining a deeper understanding of the relationship between body composition and blood pressure in the context of hemodialysis. Due to the retrospective design of this study, there were certain limitations in obtaining some parameters:

Antihypertensive Medications: Patients used a wide variety of antihypertensive drugs. As this was a retrospective analysis, systematic classification and dose adjustment analysis (e.g., specific types, doses, and medication adherence) were challenging. Therefore, these were not included as covariates in the model. We further acknowledge this as a limitation of the study.

Blood pressure variability: To minimize random error from single measurements, we used the average of all blood pressure readings taken during dialysis sessions within the three months prior to enrollment to reflect the patient's overall blood pressure burden. However, this approach cannot precisely quantify dynamic blood pressure changes during dialysis (e.g., blood pressure variability or intradialytic hypotension events). We have supplemented this point in the discussion as a direction for future research.

Ultrafiltration Volume: Your point is crucial. While this study did not directly include ultrafiltration volume in the model, one of its core findings—that total body water (TBW) is an independent positive predictor of hypertension in non-overweight male patients—provides strong indirect evidence and a physiological link to the clinical significance of ultrafiltration volume. TBW is a static indicator of volume load, whereas ultrafiltration volume is the core dynamic intervention for clinically adjusting TBW and achieving volume balance. Thus, the association between TBW and hypertension fundamentally underscores the core value of refined, individualized ultrafiltration management for blood pressure control.

In response to the above, we explicitly supplemented the following three points in the “Discussion” section (Limitations paragraph) of our paper: incomplete information on antihypertensive medications, lack of assessment for blood pressure variability, and failure to include ultrafiltration volume and other parameters in the analysis constitute the limitations of this study. Future studies will prospectively integrate these therapeutic parameters with body composition metrics to establish a comprehensive evidence chain spanning “therapeutic interventions” to “physiological states” and ultimately “clinical outcomes,” thereby providing a foundation for precision management. We sincerely appreciate your rigorous review of this study design; your insights have significantly enhanced its integrity and clinical relevance.

2) Additionally, there are some inconsistencies in wording and some typographical errors which would benefit from careful revision to improve clarity and overall presentation.

Response: Thanks for your valuable comments. We have conducted a comprehensive proofreading of the entire text for language and formatting, correcting inconsistent terminology, table formatting errors, and grammatical issues (e.g.: 1. Standardized “P-value” in tables to “P”; 2. Standardized “Lasso regression” to “LASSO regression”; 3. Typo in the fifth paragraph of the Discussion section: “Inaddition, there is a...” corrected to “In addition, there is a...”, etc.).

Attachment

Submitted filename: Response to Reviewers.docx

pone.0333566.s003.docx^{(22.7KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0333566.r003

Decision Letter 1

Diego Moriconi

4 Mar 2026

Dear Dr. Yunyan Wang,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Apr 18 2026 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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We look forward to receiving your revised manuscript.

Kind regards,

Diego Moriconi

Academic Editor

PLOS One

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If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

Additional Editor Comments:

Dear Authors,

Please revise the manuscript by carefully addressing the comments raised by the reviewer #3.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #3: All comments have been addressed

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2. Is the manuscript technically sound, and do the data support the conclusions??>

Reviewer #1: Yes

Reviewer #3: No

**********

3. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #3: I Don't Know

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Reviewer #1: Yes

Reviewer #3: No

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: Yes

Reviewer #3: No

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Reviewer #1: (No Response)

Reviewer #3: Dear Authors,

Thank you very much for submitting the manuscript entitled “Relationship between Hypertension During Dialysis and Body Composition in Non-Overweight/Overweight Obese Patients.”

This is an original study that aims to explore a possible association between intradialytic hypertension and body composition. I appreciate the effort made by the authors in addressing the comments raised by the previous reviewers.

However, several limitations may affect the robustness and clinical applicability of the findings, making the statistical analyses difficult to translate into routine clinical practice.

In particular, did the authors collect data regarding the menopausal status of the women included in the study or the use of ongoing oestrogen therapy? Oestrogen levels may influence blood pressure regulation and could therefore represent a relevant variable when interpreting sex-related differences. Including this information might help to better contextualise the observed findings.

Furthermore, can the authors hypothesise a potential explanation for the sex-related differences observed in the only statistically significant parameters identified?

Finally, it would be helpful if the authors could further clarify how these results should be interpreted in a clinical context and whether they may have practical implications for patient management.

**********

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PLoS One. 2026 Apr 21;21(4):e0333566. doi: 10.1371/journal.pone.0333566.r004

Author response to Decision Letter 2

13 Mar 2026

Additional Editor Comments:

Dear Authors,

Please revise the manuscript by carefully addressing the comments raised by the reviewer #3.

Response:

Dear Editor,

Thank you for your guidance. We have carefully revised the manuscript according to reviewer #3's comments, addressing each point raised and incorporating the corresponding modifications into the manuscript. The revisions are detailed in the response letter. We kindly request your re-review. Should any further modifications be required, we are ready to cooperate fully.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #3: All comments have been addressed

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Yes

Reviewer #3: No

Response: We appreciate the reviewer's attention. We have re-examined the data analysis process and interpretation of conclusions. This study employed LASSO regression for variable selection, combined with multivariate linear regression and logistic regression analyses stratified by gender and BMI. Results demonstrated significant correlations between specific body composition parameters (e.g., TBW, Protein, BMC, Fat) and hypertension, with statistical significance observed in specific subgroups. Despite limitations inherent to cross-sectional study designs, we believe the data provide reasonable support for our conclusions. We have further supplemented the discussion section with explanations regarding potential confounders (e.g., medication use, residual renal function) and emphasized the exploratory nature of this study, recommending future validation studies.

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #3: I Don't Know

Response: We appreciate the reviewer's attention. We have supplemented the statistical methods section with more detailed explanations. (For example: LASSO regression was used for variable selection to avoid overfitting and multicollinearity, followed by multivariate regression analysis adjusted for age. All models underwent hypothesis testing, including linearity and residual normality.)

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #3: No

Response: We appreciate the reviewers' attention. In accordance with PLOS data policy, we have uploaded a de-identified dataset as supplementary material submitted alongside the revised manuscript to ensure data transparency while safeguarding patient privacy.

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Reviewer #3: No

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Reviewer #1: (No Response)

Reviewer #3: Dear Authors,

Response: Thank you very much for submitting the manuscript entitled “Relationship between Hypertension During Dialysis and Body Composition in Non-Overweight/Overweight Obese Patients.”

However, several limitations may affect the robustness and clinical applicability of the findings, making the statistical analyses difficult to translate into routine clinical practice.

Furthermore, can the authors hypothesise a potential explanation for the sex-related differences observed in the only statistically significant parameters identified?

Response: Thanks for your valuable comments. First, we fully concur with the reviewer's perspective that menopausal status and estrogen use among female patients may significantly influence blood pressure regulation, thereby constituting potential confounding factors when interpreting gender-related differences. Unfortunately, our center's information system does not collect data on menopausal status or estrogen replacement therapy use among female patients. This represents a limitation of the study, which we have addressed in the section discussing study limitations. In future prospective studies, we will fully consider this critical recommendation by systematically collecting relevant data to more comprehensively explore the moderating role of sex hormones in the relationship between body composition and hypertension.

Secondly, we have added the following hypothesis at the end of the fifth paragraph in the Discussion section: Gender-specific mechanisms related to fat distribution patterns, sex hormone levels, and insulin resistance may account for the gender-related differences observed in this study. We hope to gain your acknowledgment and support for this point. (Content as follows: The gender-specific mechanisms underlying fat distribution patterns, sex hormone levels, and insulin resistance may account for sex-related differences. Sironi[45] et al. noted that visceral fat is closely associated with hypertension, insulin resistance, and metabolic syndrome. Postmenopausal women experience increased visceral fat accumulation due to declining estrogen levels, making adipose tissue a primary driver of hypertension. In male patients of this study, the association between TBW and Protein with hypertension may reflect more severe metabolic disorders and a state of protein-energy depletion. Conversely, the role of Fat in female patients more directly highlights the core position of adipose tissue as an endocrine organ in blood pressure regulation.)

Finally, we further elaborate on the clinical implications at the end of paragraph 6 in the Discussion section, hoping to gain your endorsement and support. (For example, in non-overweight males, monitoring total body water (TBW) and protein status aids in identifying hypertension risk; in overweight/obese females, controlling body fat may be more beneficial for blood pressure management. This suggests that individualized intervention strategies should be developed based on body composition rather than BMI alone.)

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

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Response: Yes

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PLoS One. doi: 10.1371/journal.pone.0333566.r005

Decision Letter 2

Diego Moriconi

5 Apr 2026

Relationship between Hypertension During Dialysis and Body Composition in Non-Overweight/Overweight Obese Patients

PONE-D-25-49455R2

Dear Dr. Yunyan Wang

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

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Additional Editor Comments (optional):

Dear authors, after the changes made following the instructions of the reviewers, I communicate that the paper is suitable for publication

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #3: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions??>

Reviewer #3: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #3: Yes

**********

4. Have the authors made all data underlying the findings in their manuscript fully available??>

Reviewer #3: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #3: Yes

**********

Reviewer #3: Dear Authors,

Thank you very much for submitting the revised manuscript. All the questions have been answered properly, therefore in my opinion it is suitable for publication in PlosOne.

Best regards.

**********

what does this mean? ). If published, this will include your full peer review and any attached files.). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Reviewer #3: No

**********

PLoS One. doi: 10.1371/journal.pone.0333566.r006

Acceptance letter

Diego Moriconi

PONE-D-25-49455R2

PLOS One

Dear Dr. Wang,

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS One. Congratulations! Your manuscript is now being handed over to our production team.

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Data Availability Statement

All relevant data are within the manuscript and its Supporting information files.

[pone.0333566.ref001] 1.Agarwal R, Nissenson AR, Batlle D, Coyne DW, Trout JR, Warnock DG. Prevalence, treatment, and control of hypertension in chronic hemodialysis patients in the United States. Am J Med. 2003;115(4):291–7. doi: 10.1016/s0002-9343(03)00366-8 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref002] 2.Georgianos PI, Agarwal R. Resistant hypertension in dialysis: epidemiology, diagnosis, and management. Kidney International. 2024;35(4):505–14. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref003] 3.De Lima JJG, Gowdak LHW, Reusing JO Jr, David-Neto E, Bortolotto LA. Interdialytic Blood Pressure and Risk of Cardiovascular Events and Death in Hemodialysis Patients. High Blood Press Cardiovasc Prev. 2023;30(3):235–41. doi: 10.1007/s40292-023-00575-4 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref004] 4.Bansal N, Artinian NT, Bakris G, Chang T, Cohen J, Flythe J, et al. Hypertension in Patients Treated With In-Center Maintenance Hemodialysis: Current Evidence and Future Opportunities: A Scientific Statement From the American Heart Association. Hypertension. 2023;80(6):e112–22. doi: 10.1161/HYP.0000000000000230 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref005] 5.Seravalle G, Grassi G. Obesity and hypertension. Pharmacol Res. 2017;122:1–7. doi: 10.1016/j.phrs.2017.05.013 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref006] 6.Jiang Z, Wang Y, Zhao X, Cui H, Han M, Ren X, et al. Obesity and chronic kidney disease. Am J Physiol Endocrinol Metab. 2023;324(1):E24–41. doi: 10.1152/ajpendo.00179.2022 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref007] 7.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(6):1577–85. doi: 10.4103/1319-2442.352418 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref008] 8.Body mass index and risk for end-stage renal disease. Am J Kidney Dis. 2006;144(1):21–8. [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref009] 9.Kambham N, Markowitz GS, Valeri AM, Lin J, D’Agati VD. Obesity-related glomerulopathy: an emerging epidemic. Kidney Int. 2001;59(4):1498–509. doi: 10.1046/j.1523-1755.2001.0590041498.x [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref010] 10.Kalaitzidis RG, Siamopoulos KC. The role of obesity in kidney disease: recent findings and potential mechanisms. Int Urol Nephrol. 2011;43(3):771–84. doi: 10.1007/s11255-011-9974-1 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref011] 11.Axelsson J, Rashid Qureshi A, Suliman ME, Honda H, Pecoits-Filho R, Heimbürger O, et al. Truncal fat mass as a contributor to inflammation in end-stage renal disease. Am J Clin Nutr. 2004;80(5):1222–9. doi: 10.1093/ajcn/80.5.1222 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref012] 12.Kalantar-Zadeh K, Block G, Humphreys MH, Kopple JD. Reverse epidemiology of cardiovascular risk factors in maintenance dialysis patients. Kidney Int. 2003;63(3):793–808. doi: 10.1046/j.1523-1755.2003.00803.x [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref013] 13.Deger SM, Ellis CD, Bian A, Shintani A, Ikizler TA, Hung AM. Obesity, diabetes and survival in maintenance hemodialysis patients. Ren Fail. 2014;36(4):546–51. doi: 10.3109/0886022X.2013.876351 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref014] 14.Mathilakath NC, Selvaraj J, Parameswaran S, Viswanathan S, Pillai V, Kt H. Prevalence of Overhydration in Patients on Maintenance Haemodialysis As Determined by Body Composition Monitor and Effects of Attaining Target Dry Weight. Cureus. 2022;14(9):e29509. doi: 10.7759/cureus.29509 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref015] 15.Dahel-Mekhancha CC, Rolland-Cachera M-F, Botton J, Karoune R, Sersar I, Yagoubi-Benatallah L, et al. Body composition and anthropometric indicators as predictors of blood pressure: a cross-sectional study conducted in young Algerian adults. Br J Nutr. 2023;129(11):1993–2000. doi: 10.1017/S0007114522002719 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref016] 16.Korhonen PE, Mikkola T, Kautiainen H, Eriksson JG. Both lean and fat body mass associate with blood pressure. Eur J Intern Med. 2021;91:40–4. doi: 10.1016/j.ejim.2021.04.025 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref017] 17.Tian M, Lan Q, Yuan J, He P, Yu F, Long C, et al. Low Lean Tissue Index and Muscle Strength Combined with High Fat Tissue Index Are Associated with Cardiovascular Disease-Related Hospitalisation in Patients on Haemodialysis. Cardiorenal Med. 2023;13(1):363–71. doi: 10.1159/000534399 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref018] 18.Tian M, Zha Y, Qie S, Lin X, Yuan J. Association of Body Composition and Intradialytic Hypotension in Hemodialysis Patients. Blood Purif. 2020;49(3):334–40. doi: 10.1159/000504245 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref019] 19.Burlyaeva EA, Prunceva TA, Semenov MM, Stakhanova AA, Korotkova TN, Elizarova EV. Body composition and basal metabolic rate in overweight and obese patients. Vopr Pitan. 2022;91(5):78–86. doi: 10.33029/0042-8833-2022-91-5-78-86 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref020] 20.Agarwal R, Brim NJ, Mahenthiran J, Andersen MJ, Saha C. Out-of-hemodialysis-unit blood pressure is a superior determinant of left ventricular hypertrophy. Hypertension. 2006;47(1):62–8. doi: 10.1161/01.HYP.0000196279.29758.f4 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref021] 21.Agarwal R. Blood pressure and mortality among hemodialysis patients. Hypertension. 2010;55(3):762–8. doi: 10.1161/HYPERTENSIONAHA.109.144899 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref022] 22.Miskulin DC, Gassman J, Schrader R, Gul A, Jhamb M, Ploth DW, et al. BP in Dialysis: Results of a Pilot Study. J Am Soc Nephrol. 2018;29(1):307–16. doi: 10.1681/ASN.2017020135 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref023] 23.Cheung AK, Chang TI, Cushman WC, Furth SL, Hou FF, Ix JH, et al. Executive summary of the KDIGO 2021 Clinical Practice Guideline for the Management of Blood Pressure in Chronic Kidney Disease. Kidney Int. 2021;99(3):559–69. doi: 10.1016/j.kint.2020.10.026 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref024] 24.Zierle-Ghosh A, Jan A. Physiology, Body Mass Index. Treasure Island (FL): StatPearls. ineligible companies. Disclosure: Arif Jan declares no relevant financial relationships with ineligible companies.: StatPearls Publishing Copyright © 2025, StatPearls Publishing LLC.; 2025. [Google Scholar]

[pone.0333566.ref025] 25.Spahia N, Rroji M, Idrizi A, Spasovski G, Barbullushi M. Sodium and water dynamics in the progression of chronic kidney disease: mechanisms and clinical significance. Int Urol Nephrol. 2024;56(6):1953–63. doi: 10.1007/s11255-023-03903-8 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref026] 26.Flythe JE, Chang TI, Gallagher MP, Lindley E, Madero M, Sarafidis PA, et al. Blood pressure and volume management in dialysis: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference. Kidney Int. 2020;97(5):861–76. doi: 10.1016/j.kint.2020.01.046 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref027] 27.Weiner DE, Brunelli SM, Hunt A, Schiller B, Glassock R, Maddux FW, et al. Improving clinical outcomes among hemodialysis patients: a proposal for a “volume first” approach from the chief medical officers of US dialysis providers. Am J Kidney Dis. 2014;64(5):685–95. doi: 10.1053/j.ajkd.2014.07.003 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref028] 28.Lambers Heerspink HJ, Navis G, Ritz E. Salt intake in kidney disease--a missed therapeutic opportunity? Nephrology, Dialysis, Transplantation. 2012;27(9):3435–42. [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref029] 29.Canaud B, Chazot C, Koomans J, Collins A. Fluid and hemodynamic management in hemodialysis patients: challenges and opportunities. J Bras Nefrol. 2019;41(4):550–9. doi: 10.1590/2175-8239-JBN-2019-0135 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref030] 30.Zoccali C, Mallamaci F. Mapping Progress in Reducing Cardiovascular Risk with Kidney Disease: Managing Volume Overload. Clin J Am Soc Nephrol. 2018;13(9):1432–4. doi: 10.2215/CJN.01360118 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref031] 31.Georgianos PI, Agarwal R. Resistant Hypertension in Dialysis: Epidemiology, Diagnosis, and Management. J Am Soc Nephrol. 2024;35(4):505–14. doi: 10.1681/ASN.0000000000000315 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref032] 32.Ikizler TA, Cano NJ, Franch H, Fouque D, Himmelfarb J, Kalantar-Zadeh K, et al. Prevention and treatment of protein energy wasting in chronic kidney disease patients: a consensus statement by the International Society of Renal Nutrition and Metabolism. Kidney Int. 2013;84(6):1096–107. doi: 10.1038/ki.2013.147 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref033] 33.Hanna RM, Ghobry L, Wassef O, Rhee CM, Kalantar-Zadeh K. A practical approach to nutrition, protein-energy wasting, sarcopenia, and cachexia in patients with chronic kidney disease. Blood Purif. 2020;49(1–2):202–11. [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref034] 34.Cappuccio FP, Meilahn E, Zmuda JM, Cauley JA. High blood pressure and bone-mineral loss in elderly white women: a prospective study. The Lancet. 1999;354(9183):971–5. doi: 10.1016/s0140-6736(99)01437-3 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref035] 35.Titze J. Bone mineral content and blood pressure: What is the pathophysiologic link? Am J Hypertens. 2006;19(8):877–8. doi: 10.1016/j.amjhyper.2006.01.017 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref036] 36.Afghani A, Johnson CA. Resting blood pressure and bone mineral content are inversely related in overweight and obese Hispanic women. Am J Hypertens. 2006;19(3):286–92. doi: 10.1016/j.amjhyper.2005.10.024 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref037] 37.Zhu J-G, Chen J-B, Cheng B-C, Lee C-H, Long G, Chien Y-S. Association between Extreme Values of Markers of Chronic Kidney Disease: Mineral and Bone Disorder and 5-Year Mortality among Prevalent Hemodialysis Patients. Blood Purif. 2018;45(1–3):1–7. doi: 10.1159/000478972 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref038] 38.Li W, Xu R, Wang Y, Shen J, Li Z, Yu X, et al. Association of body mass index and uncontrolled blood pressure with cardiovascular mortality in peritoneal dialysis patients. J Hum Hypertens. 2019;33(2):106–14. doi: 10.1038/s41371-018-0107-5 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref039] 39.Fahed G, Aoun L, Bou Zerdan M, Allam S, Bou Zerdan M, Bouferraa Y. Metabolic syndrome: updates on pathophysiology and management in 2021. Int J Mol Sci. 2022;23(2). [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref040] 40.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(1):62–9. doi: 10.4103/1319-2442.279962 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref041] 41.Jialin W, Yi Z, Weijie Y. Relationship between body mass index and mortality in hemodialysis patients: a meta-analysis. Nephron Clin Pract. 2012;121(3–4):c102-11. doi: 10.1159/000345159 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref042] 42.Hou Y, Yang S. Association of risk factors for high blood pressure across 46 low- and middle-income countries: A multi-country cross-sectional analysis. J Glob Health. 2024;14:04087. doi: 10.7189/jogh.14.04087 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref043] 43.Xu C, Zhong J, Zhu H, Hu R, Fang L, Wang M, et al. Independent and interactive associations of heart rate and body mass index or blood pressure with type 2 diabetes mellitus incidence: A prospective cohort study. J Diabetes Investig. 2019;10(4):1068–74. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0333566.ref044] 44.Syme C, Shin J, Richer L, Gaudet D, Paus T, Pausova Z. Sex Differences in Blood Pressure Hemodynamics in Middle-Aged Adults With Overweight and Obesity. Hypertension. 2019;74(2):407–12. doi: 10.1161/HYPERTENSIONAHA.119.13058 [DOI] [PubMed] [Google Scholar]

[pone.0333566.ref045] 45.Anna Maria S, Rosa S, Franco F, Amalia G. Ectopic fat storage, insulin resistance, and hypertension. Current Pharmaceutical Design. 2011;17(28):3074–80. [DOI] [PubMed] [Google Scholar]

PERMALINK

Relationship between hypertension during dialysis and body composition in non-overweight/overweight obese patients

Jiaoyan Chen

Xianqiong Lu

Jurong Yang

Jingrong Peng

Maodi She

Yunyan Wang

Roles

Abstract

Introduction

Materials and methods

Participants

Body composition measurement

Blood pressure data collection and definition of hypertension

Definition of non-overweight/overweight obese

Statistical analysis

Result

Fig 1. Process of screening variables by LASSO regression modeling.

Table 1. Comparison of patient characteristics between male and female MHD patients.

Table 2. Relationship of SBP with TBW, Protein, BMC, and Fat.

Table 3. Relationship of DBP with TBW, Protein, BMC, and Fat.

Fig 2. Association of TBW, Protein, BMC, and Fat with hypertension risk.

Discussion

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Diego Moriconi

Roles

Author response to Decision Letter 1

Decision Letter 1

Diego Moriconi

Roles

Author response to Decision Letter 2

Decision Letter 2

Diego Moriconi

Roles

Acceptance letter

Diego Moriconi

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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