Could long-term dialysis vintage and abnormal calcium, phosphorus and iPTH control accelerate aging among the maintenance hemodialysis population?

Abstract

Objective

Aging is a complex process of physiological dysregulation of the body system and is common in hemodialysis patients. However, limited studies have investigated the links between dialysis vintage, calcium, phosphorus, and iPTH control and aging. The purpose of the current study was to examine these associations.

Methods

During 2020, a cross-sectional study was conducted in 3025 hemodialysis patients from 27 centers in Anhui Province, China. Biological age was calculated by a formula using chronological age and clinical indicators. The absence of the target range for serum phosphorus (0.87–1.45 mmol/L), corrected calcium (2.1–2.5 mmol/L) and iPTH (130–585 pg/mL) were identified as abnormal calcium, phosphorus, and iPTH control.

Results

A total of 1131 hemodialysis patients were included, 59.2% of whom were males (669/1131). The mean (standard deviation) of actual age and biological age were 56.07 (12.79) years and 66.94 (25.88), respectively. The median of dialysis vintage was 4.3 years. After adjusting for the confounders, linear regression models showed patients with abnormal calcium, phosphorus, and iPTH control and on hemodialysis for less than 4.3 years (B = 0.211, p = .002) or on hemodialysis for 4.3 years or more (B = 0.302, p < .001), patients with normal calcium, phosphorus, and iPTH control and on hemodialysis for 4.3 years or more (B = 0.087, p = .013) had a higher biological age.

Conclusion

Our findings support the hypothesis that long-term hemodialysis and abnormal calcium, phosphorus, and iPTH control may accelerate aging in the hemodialysis population. Further studies are warrant to verify the significance of maintaining normal calcium-phosphorus metabolism in aging.

1. Introduction

Aging is a complex process of multi-system physiological disorders, which are divided into two main types: physiological aging and pathological aging [1]. Physiological aging refers to the natural aging that occurs when a person suffers unavoidable age and time-related changes, whereas pathological aging is associated with a variety of physical or mental disorders and usually encompasses acute or chronic diseases, environmental factors, etc. [2–5]. Aging is strongly associated with the accelerated development of chronic diseases, and it is also considered a major correlate of risk for many chronic diseases and mortality [1,6]. However, individuals of the same age may age at different rates and experience significant individual variations in their health outcomes. [7]. Biological age is an indicator obtained by calculating from biological data of the organism and is a more accurate reflection of the health status of the organism compared to the actual age [8]. The current calculation of biological age consists of nine clinical biomarkers that have been selected for their ability to estimate mortality and morbidity [6]. Such aging indicators are important for the early detection of individuals who deviate from healthy aging trends, for assessing the outcome of aging delay interventions, and for promoting health outcomes in populations [6,9].

End-stage kidney disease (ESKD), which is the final stage of renal deterioration characterized by a GFR <15 mL/min/1.73m² and symptoms of renal failure including uremia, metabolic acidosis, anemia, electrolyte imbalance, and endocrine disorders [10,11]. Hemodialysis is the main modality for ESKD patients in most countries [12]. The Chinese Doctors Association’s Nephrologists Branch reported in 2022 that hemodialysis patients climbed from 283,581 to 749,573 between 2013 and 2021. ESKD patients usually underwent hemodialysis to reduce the burden of disease and prolong their life span or chronological age. However, in ESKD patients, as renal function declines, metabolic disturbance in calcium, phosphorus, or intact parathyroid hormone (iPTH) is one of the common comorbidities [7]. It is one of the most important clinical features of hemodialysis patients and has a serious impact on life quality and health outcomes [13,14]. Few studies have been conducted to determine whether long-term dialysis vintage and abnormal calcium, phosphorus and iPTH control affect pathological aging.

Previous studies have identified an interaction between aging and renal disease, with CKD accelerating aging through a variety of mechanisms including effects on cognitive function and cardiovascular disease [15,16]. However, few studies have focused on the correlation between dialysis vintage, calcium-phosphorus metabolism, and aging, particularly in the hemodialysis population. It is therefore important to assess the conditions of aging in the hemodialysis population and provide timely and effective interventions for those with advanced aging, particularly in the context of the increasing number of people on dialysis in recent years, and to improve the quality of life and health outcomes for them. Therefore, this study hypothesized that the biological age of the long-term hemodialysis population with abnormal calcium, phosphorus and iPTH control is higher. A cross-sectional study was conducted in 2020 at 27 hemodialysis centers in Anhui Province, China, to analyze whether long-term dialysis vintage and abnormal calcium, phosphorus and iPTH control could accelerate aging among the hemodialysis population.

2. Materials and methods

2.1. Participants

A total of 3025 patients undergoing hemodialysis were recruited from 27 hemodialysis centers in Anhui Province, China, during the period from 1st January 2020 to 31st December 2020. None of the patients in this study were infected with COVID-19 before data collection. Inclusion criteria for participants were age ≥18 years, regular hemodialysis for more than 3 months, and providing informed consent. Patients under the age of 18 years or who refused to participate or were defined as having: NYHA class III or higher heart failure; complex with severe liver, lung, brain, and other organ failures diseases such as cirrhosis, chronic respiratory failure, and hemiplegia; HIV infection or AIDS; and psychiatric complications of malignancy were excluded. A total of 1894 patients were excluded because of the lack of data on C-reactive protein (CRP) and the failure to derive biological age. Finally, 1131 patients were analyzed in the study. The flow chart of the selection of participants was shown in Figure 1.

Figure 1.

Flow chart of participants.

This study was approved by the Ethics Committee of The Second Hospital of Anhui Medical University (No. PJ-YX2020-006). Electronic informed consent was obtained from all participants before completing the survey. The study was conducted following the principles of the Declaration of Helsinki.

2.2. Research methods

An online platform named ‘h6world’ (website: https://h6world.cn/website/index.html) supported by the Clinical Big Data Platform Research Group at Peking University was used to collect data. Before the survey, physicians, nurses, or investigators at each center received training. Each center logged into the platform for data entry. All data were aggregated to the project leader and checked by quality controllers, including demographic characteristics (e.g., gender, age, family residence, education, family income, marital status, etc.), behaviors (e.g., smoking, drinking, etc.), hemodialysis status, height, weight, dialysis vintage, anxiety, medication use, cardiovascular events, comorbidities, and laboratory data.

2.3. Laboratory data

Laboratory analysis was performed on fasting venous blood samples collected before dialysis. Serum albumin (Alb), mean red blood cell volume (MCV), creatinine (Cr), glucose (Glu), CRP, red blood cell distribution width (RDW), white blood cells (WBC), lymphocyte percentage, alkaline phosphatase (ALP), serum corrected calcium, serum phosphorus, and iPTH obtained by the second generation PTH assay were measured by the biochemical auto-analyzer in the laboratory department of each center.

2.4. Guidelines for calcium, phosphorus and iPTH control

The Chinese CKD-MBD diagnosis and treatment guidelines released in 2019 recommend a target range of 2.1–2.5 mmol/L (8.4–10.0 mg/dL), 0.87–1.45 mmol/L (2.7–4.5 mg/dL) and 2-9 times the upper limit of normal (130–585 pg/mL) for serum corrected calcium, phosphorus and iPTH in patients undergoing hemodialysis, respectively [6]. When serum Alb was below 40 g/L, a correction formula for serum calcium was used: corrected calcium (mmol/L) = total serum calcium (mmol/L) + 0.2 × [4-Alb(g/L)/10]. Only when the levels of serum corrected calcium, phosphorus, and iPTH all reached the target range, the patients were identified as the normal group, and others were divided into the abnormal group with abnormal calcium, phosphorus and iPTH control.

2.5. Calculation for biological age

Biological age was calculated by the formula [6]:

$$\text{Biological}\text{age}=141.50225+\frac{-\text{In}\left[-0.00553\times \text{In}\left(1\text{-Mortality}\right)\right]}{0.090165}$$

where

$$\begin{array}{l}\text{Mortality}=1-{\text{e}}^{-{\text{e}}^{\text{xb}}\left[\exp \left(120\times \gamma \right)-\text{\hspace{0.17em}1}\right]/\gamma }\\ \gamma =\text{0}\text{.007692}\end{array}$$

xb = −19.907 − 0.0336 × albumin + 0.0095 × creatinine + 0.1953 × glucose + 0.0954 × ln(C-reactive protein) − 0.012 × lymphocyte percentage + 0.0268 × mean red blood cell volume + 0.3306 × red blood cell distribution width + 0.00188 × alkaline phosphatase + 0.0554 × white blood cell count + 0.0804 × actual age

2.6. Statistical analysis

The normally distributed data were expressed by the mean and standard deviation (SD), and the skewed data were expressed by the median and quartiles (Q1, Q3). Categorical data were expressed as frequencies (n) and percentages (%). Dialysis vintage was divided into two categories based on the median of 4.3 years. Two independent samples t-tests and nonparametric tests were used to compare the differences in indicators between different groups. Multivariate linear regression models were applied to analyze the associations of dialysis vintage and calcium, phosphorus, and iPTH control with biological age. All data analysis were performed by SPSS 26.0. All statistical tests were two-tailed, and significance was set at p < .05.

3. Results

3.1. Characteristics of patients undergoing hemodialysis

In this study, Table 1 shows that 1131 hemodialysis patients were included, 669 (59.2%) were males. The mean age of the patients was 56.07 ± 12.79 years and the mean biological age was 66.94 ± 25.88 years. The median of dialysis vintage was 4.3 (2.1, 7.3) years. Males had a higher biological age of 71.15 ± 26.07 years, while females had a lower biological age of 60.85 ± 24.38 years. Single patients had a lower biological age of 61.71 ± 29.54 years compared to those who were married, with a biological age of 67.69 ± 25.25 years. Patients with a lower education level (below junior high school) had a lower biological age of 64.84 ± 25.31 years, while those with junior high school and above had a higher biological age of 68.85 ± 26.27 years. Patients living in urban areas had a higher biological age of 70.52 ± 26.66 years, compared to those living in rural areas, who had a biological age of 61.87 ± 23.87 years. Smokers had a higher biological age of 73.03 ± 25.16 years compared to nonsmokers, who had a biological age of 65.97 ± 25.88 years. Patients who were current drinkers had a higher biological age of 71.32 ± 27.58 years than those who were nondrinkers. Patients with hypertension or diabetes had a higher biological age of 67.84 ± 25.91 or 71.60 ± 24.85 years. Patients who took medication for calcium-phosphorus metabolism disorders had a higher biological age of 68.60 ± 24.18 years compared to non-users, who had a biological age of 65.14 ± 27.52 years. Patients who took high-flux dialysis protocol had a higher biological age of 70.19 ± 24.88 years. Dialysis vintage (r = 0.073, p = .015), BMI (r = 0.145, p < .001), serum phosphorus (r = 0.301, p < .001) and iPTH (r = 0.083, p = .005) were positively correlated with biological age. Serum correct calcium (r = −0.068, p = .022) was negatively correlated with biological age.

Table 1.

Distribution of biological age in different characteristics of patients undergoing hemodialysis (n = 1131).

	Median (Q1, Q3)/n	Biological age			Calcium, phosphorus and iPTH control [n (%)]
Characteristics	(%)	M ± SD	t/r value	p value	Normal n = 87	Abnormal n = 1044	t/Z value	p value
Gender			6.705	<.001			0.122	.727
Males	669 (59.2)	71.15 ± 26.07			53(60.9)	616(59.0)
Females	462 (40.8)	60.85 ± 24.38			34(39.1)	428(41.0)
Family residence			−5.716	<.001			0.462	.497
Rural	468 (41.4)	61.87 ± 23.87			33(37.9)	435(41.7)
Urban	663 (58.6)	70.52 ± 26.66			54(62.1)	609(58.3)
Family income			−1.781	.075			1.875	.171
≤¥4000	861 (76.1)	66.17 ± 25.71			61(70.1)	800(76.6)
>¥4000	270 (23.9)	69.38 ± 26.34			26(29.9)	244(23.4)
Marital status			2.291	.023			0.969	.325
Married	989 (87.4)	67.69 ± 25.25			79(90.8)	910(87.2)
Single	142 (12.6)	61.71 ± 29.54			8(9.2)	134(12.8)
Educational levels			−2.610	.009			0.625	.429
Below junior high school	539 (47.7)	64.84 ± 25.31			42(48.3)	494(47.3)
Junior high school and above	592 (52.3)	68.85 ± 26.27			45(51.7)	559(52.7)
Smoking			3.166	.002			0.389	.533
Yes	155 (13.7)	73.03 ± 25.16			10(11.5)	145(13.9)
No	976 (86.3)	65.97 ± 25.88			77(88.5)	899(86.1)
Drinking			2.056	.040			0.122	.726
Yes	130 (11.5)	71.32 ± 27.58			11(12.6)	119(11.4)
No	1001 (88.5)	66.37 ± 25.62			76(87.4)	925(88.6)
Cardiovascular events			−0.903	.367			0.791	.374
Yes	181 (16.0)	65.35 ± 25.36			11(12.6)	170(16.3)
No	950 (84.0)	67.35 ± 25.36			76(87.4)	874(83.7)
Cerebrovascular events			1.627	.104			1.891	.169
Yes	199 (17.6)	69.65 ± 26.47			20(23.0)	179(17.1)
No	932 (82.4)	66.36 ± 25.74			67(77.0)	865(82.9)
Medication for calcium-phosphorus metabolic disorders			2.244	.025			4.251	.039
Yes	588 (52.0)	68.60 ± 24.18			36(41.4)	552(52.9)
No	543 (48.0)	65.14 ± 27.52			51(58.6)	492(47.1)
Diabetes			−3.713	<.001			0.765	.385
Yes	306 (27.1)	71.60 ± 24.85			27(31.0)	279(26.7)
No	825 (62.9)	65.20 ± 26.06			60(69.0)	765(73.3)
Antihypertensive drugs			0.612	.541			0.317	.574
Yes	749 (66.2)	67.27 ± 25.30			60(69.0)	689(66.0)
No	382 (33.8)	66.28 ± 27.03			27(31.0)	355(34.0)
Hypolipidemic drugs			1.921	.055			0.893	.345
Yes	240 (21.2)	69.78 ± 24.96			15(17.2)	225(21.6)
No	891 (78.8)	66.17 ± 26.09			72(82.8)	819(78.4)
Anxiety			0.605	.545			0.169	.681
Yes	294 (26.0)	67.72 ± 25.19			21(24.1)	273(26.1)
No	837 (74.0)	66.66 ± 26.13			66(75.6)	771(73.9)
Hypertension			2.435	.015			0.523	.470
Yes	917 (81.1)	67.84 ± 25.91			68(78.2)	849(81.3)
No	214 (18.9)	63.07 ± 25.46			19(21.8)	195(18.7)
Dialysis duration			0.426	.653			1.059	.587
3 h	9 (0.8)	59.42 ± 21.70			1(1.1)	8(0.8)
4 h	1120(99.0)	66.99 ± 25.91			86(98.9)	1034(99.0)
5 h	2(0.2)	72.38 ± 39.98			0(0.0)	2(0.2)
Numbers of dialysis per week			1.105	.346			5.786	.161
1	1(0.1)				0(0.0)	1(0.1)
2	125(10.6)	69.40 ± 24.60			5(5.7)	120(11.5)
3	1001(88.5)	66.66 ± 26.34			81(93.1)	920(88.1)
4	4(0.4)	68.22 ± 24.29			1(1.1)	3(0.3)
Dialysis protocol			17.841	<.001			6.971	.031
Low-flux dialysis	261(23.1)	67.26 ± 26.36			30(34.5)	231(22.1)
High-flux dialysis	612(54.1)	70.19 ± 24.88			41(47.1)	571(54.7)
Hemodialysis and hemofiltration > once per week	258(22.8)	58.89 ± 26.10			16(18.4)	242(23.2)
Dialysis vintage (years)	4.3 (2.1, 7.3)		0.073	.015	2.9(1.4,5,5)	4.5(2.2,7.5)	−2.995	.003
BMI (kg/m2)	21.49 (19.27, 23.74)		0.145	<.001	20.28(18.89,23.44)	21.55(19.35,23.80)	−1.904	.057
Correct calcium (mmol/L)	2.31 (2.17, 2.45)		−0.068	.022	2.29(2.21,2.39)	2.31(2.16,2.46)	−0.836	.403
Serum phosphorus (mmol/L)	1.82 (1.45, 2.22)		0.301	<0.001	1.27(1.15,1.34)	1.89(1.56,2.25)	−11.998	<.001
iPTH (pg/mL)	280.00 (126.00,480.10)		0.083	.005	270.80 (193.00,348.10)	281.18 (117.00,502.40)	−0.273	.784

Shorter dialysis vintage, lower serum phosphorus level, and a higher rate of medication for calcium-phosphorus metabolic disorders were found among patients with abnormal calcium, phosphorus, and iPTH control group. In the abnormal calcium, phosphorus, and iPTH control group, a lower rate of low-flux dialysis (22.1%), higher rates of in high-flux dialysis (54.7%) and hemodialysis & hemofiltration > once per week (23.2%) were observed.

3.2. Correct calcium, serum phosphorus and iPTH levels in different stratifies of calcium, phosphorus and iPTH control and dialysis vintage

Table S1 shows the correct calcium, serum phosphorus and iPTH levels in different stratifies of calcium, phosphorus, and iPTH control and dialysis vintage. Correct calcium, serum phosphorus, and iPTH levels were the highest in patients undergoing hemodialysis for 4.3 years or more and with abnormal calcium, phosphorus, and iPTH control.

3.3. The differences in biological age between different groups

Table 2 shows the differences in biological age between different groups. There were 573 patients undergoing long-term dialysis vintage, which accounted for 50.7% of the total study population; 1044 (92.3%) patients were classified as having abnormal calcium, phosphorus, and iPTH control. The rates of abnormal correct calcium, serum phosphorus, and iPTH were 34.5%, 77.4%, and 44.5%, respectively. The mean biological age was 67.55 ± 25.73 years in patients with abnormal calcium, phosphorus, and iPTH control, which was higher than that of normal patients. Compared to patients with normal levels of correct calcium, serum phosphorus or iPTH, patients with abnormal correct calcium level or iPTH level had a lower biological age of 64.80 ± 26.25 years or 64.11 ± 26.25 years; but a higher biological age of 69.83 ± 24.69 years was found in patients with abnormal serum phosphorus level.

Table 2.

The differences in biological age between different groups.

Variables	Total [n(%)]	Biological age	t value	p value
Dialysis vintage (years)			1.422	.155
<4.3 years	558 (49.3)	65.83 ± 25.92
≥4.3 years	573 (50.7)	68.02 ± 25.82
Calcium, phosphorus and iPTH control			−2.683	.009
Normal	87 (7.7)	59.56 ± 26.79
Abnormal	1044 (92.3)	67.55 ± 25.73
Correct calcium (mmol/L)			2.017	.044
Normal	741(65.5)	68.06 ± 25.63
Abnormal	390(34.5)	64.80 ± 26.25
Serum phosphorus (mmol/L)			−7.111	<.001
Normal	256(22.6)	57.03 ± 27.44
Abnormal	875(77.4)	69.83 ± 24.69
iPTH (pg/mL)			3.305	.001
Normal	628(55.5)	69.20 ± 25.38
Abnormal	503(44.5)	64.11 ± 26.25

3.4. Linear regression analysis of independent associations of dialysis vintage or calcium, phosphorus and iPTH control with biological age

Table 3 shows the linear regressions of independent associations of dialysis vintage or calcium, phosphorus, and iPTH control with biological age. After controlling for gender, family residence, educational levels, marital status, smoking, alcohol consumption, dialysis protocol, diabetes, hypertension, medication for calcium-phosphorus metabolism disorders, and BMI in model 2, the results showed that dialysis for 4.3 years or more was positively associated with biological age (B = 0.098, p = .001). Patients with abnormal calcium, phosphorus and iPTH control showed increased risk of higher biological age (B = 0.092, p = .001).

Table 3.

Linear regression analysis of independent associations of dialysis vintage or calcium, phosphorus and iPTH control with biological age.

Variables	Crude model				Adjusted model
	B	p value	t value	95% CI	B	p value	t value	95% CI
Dialysis vintage
<4.3 years	Ref.
≥4.3 years	0.042	.155	1.422	−0.831-5.207	0.098	.001	3.291	2.056–8.127
Calcium, phosphorus and iPTH control
Normal	Ref.
Abnormal	0.082	.006	2.777	2.346–13.647	0.092	.001	3.245	3.542–14.373
Correct calcium (mmol/L)	0.007	.816	0.233	−2.054 to 2.607	0.008	.789	0.267	−1.915 to 2.520
Serum phosphorus (mmol/L)	0.294	<.001	10.323	10.852–15.945	0.302	<.001	11.664	11.954–16.789
iPTH (pg/mL)	0.034	.251	1.149	−0.0002 to 0.006	0.043	.136	1.493	−0.001 to 0.006

B: regression coefficient; CI: confidence interval.

Crude model was not adjusted by any variables, adjusted model was adjusted by gender, family residence, educational levels, marital status, smoking, alcohol consumption, dialysis protocol, diabetes, hypertension, medication for calcium-phosphorus metabolism disorders, and BMI.

3.5. Linear regression analysis of the associations of dialysis vintage and abnormal calcium, phosphorus and iPTH control with biological age

Table 4 displays the multivariate linear regressions of the associations of dialysis vintage and calcium, phosphorus and iPTH control with biological age. After controlling for gender, family residence, educational levels, marital status, smoking, alcohol consumption, dialysis protocol, diabetes, hypertension, medication for calcium-phosphorus metabolism disorders, and BMI, the results indicated that compared to patients undergoing hemodialysis less than 4.3 years without normal calcium, phosphorus, and iPTH control, patients undergoing hemodialysis less than 4.3 years with abnormal calcium, phosphorus, and iPTH control were more likely to be with higher biological age (B = 0.211, p = .002). Patients undergoing long-term hemodialysis with normal calcium, phosphorus and iPTH control were positively associated with biological age (B = 0.087, p = .013), and there was a stronger positive association of long-term hemodialysis and abnormal calcium, phosphorus and iPTH control with biological age (B = 0.302, p < .001).

Table 4.

Linear regression analysis of the associations of dialysis vintage and calcium, phosphorus and iPTH control with biological age.. Linear regression analysis of the associations of dialysis vintage and calcium, phosphorus and iPTH control with biological age.

Dialysis vintage	Calcium, phosphorus and iPTH control	Crude model				Adjusted model
		B	p value	t value	95% CI	B	p value	t value	95% CI
<4.3 years	Normal	Ref.
	Abnormal	0.234	.001	3.294	4.915–19.396	0.211	.002	3.151	4.146–17.835
≥4.3 years	Normal	0.081	.030	2.179	1.235–23.581	0.087	.013	2.492	2.857–24.026
	Abnormal	0.255	<.001	3.592	5.996–20.431	0.302	<.001	4.441	8.730–22.547

B: regression coefficient; CI: confidence interval.

Crude model was not adjusted by any variables, adjusted model was adjusted by gender, family residence, educational levels, marital status, smoking, alcohol consumption, dialysis protocol, diabetes, hypertension, medication for calcium-phosphorus metabolism disorders, and BMI.

3.6. External validity analysis

External validity analyses were performed on the excluded and included samples. As shown in Supplementary Table S2, patients in the included group were older and had a shorter dialysis vintage. In addition, the percentage of patients living in rural areas was higher in the included group than that of the excluded group. Compared to the excluded group, the rates of hypertension, correct calcium, and phosphorus normal levels were higher in the included group, but the rate of medication use for calcium-phosphorus metabolism disorders was lower in the included group. All the differences were statistically significant (p < .05).

4. Discussion

This study conducted in 27 hemodialysis centers in Anhui Province, China, aimed to analyze the correlation between dialysis vintage, calcium, phosphorus and iPTH control and aging in hemodialysis patients. The results revealed that long-term dialysis vintage and abnormal calcium, phosphorus and iPTH control were both related to accelerated aging. Compared to patients with hemodialysis for less than 4.3 years and normal calcium, phosphorus and iPTH control, patients with long-term hemodialysis and abnormal calcium, phosphorus and iPTH control had accelerated aging. The findings suggest that normal calcium, phosphorus, and iPTH control may have a beneficial effect on slowing the aging process in hemodialysis patients.

Aging not only impairs sensory, motor, and cognitive functions and reduces the quality of life, but is also strongly associated with multiple chronic diseases and mortality risk [17]. ESKD contributes to premature aging, which providing an indication that early identification of patients with premature aging, timely intervention, and delaying their aging to promote better health outcomes is full of importance [13,18].

Abnormal calcium, phosphorus, and iPTH control in hemodialysis patients can contribute to CKD-MBD and accelerate aging. Patients with CKD-MBD are more prone to the formation of calcium phosphate crystals and altered pyrophosphates, leading to abnormal deposition of calcium phosphate salts in cardiovascular tissues, resulting in vascular calcification and accelerated vascular aging [19]. Moreover, the expression level of the klotho gene, which is an aging inhibitor gene, decreases in patients with chronic renal failure, affecting the function of phosphate excretion, and accelerating aging through protein-bound urotoxins [20–22]. Animal experiments have shown that calcium-phosphate metabolism disorders affect aging, where mice exhibit a complex aging phenotype after the knockout of the klotho gene, while these mice placed on a low phosphate diet are protected from premature aging [23,24]. Similarly, our study found that hemodialysis patients with abnormal calcium, phosphorus and iPTH control had higher biological age. A 10-year cohort study also found that for every 1 mg/dL increase in serum phosphorus in hemodialysis patients, the increased risk of sudden death by 23.0% and peripheral arterial disease by 24.0%, which also supported our results [25,26]. Interestingly, a separate study found that elderly ESKD patients receiving secondary parathyroid function therapy had a lower risk of dementia, indicating that the treatment of calcium and phosphorus metabolism disorders may decrease cognitive aging. However, further research is needed to better understand the underlying pathways and to develop new strategies for delaying the aging process in ESKD patients [27]. The results suggested that long-term hemodialysis may accelerate aging, one potential mechanism could be explained that repeated stimulation of monocytes by long-term hemodialysis may shorten telomere length, increase p53 expression, CD14dim/CD16bright expression, and overproduce interleukin in monocytes [28].

We also found that unhealthy lifestyle habits and some demographic characteristics were associated with aging in hemodialysis patients. Patients reported smoking and drinking had accelerated aging than those who did not smoke and drink, which is consistent with previous studies [29,30]. Single patients have younger biological age and lower aging, but this is inconsistent with the results of Galkin et al. [31]. The sample size of single patients included in this study was small, and also included patients who were divorced and widowed, etc. Another study reported that marital satisfaction played an important role in the effects of aging and that only a satisfactory marriage increased its potential benefits and thus reduces its health risks, but this was lacking in our study [32]. We also found lower levels of aging in patients from rural areas, however, this differs from some studies in Japan and the United States, which concluded that urban residents have higher physical health status [33,34]. Our results are similar to a Portuguese study, which indicated rural residents presented higher quality of life and functional fitness than older individuals living in urban areas, and this may be due to the differences in geographical feature, health care, and the type of daily life activities between countries [35]. A positive correlation between BMI and aging was also observed in our study, and cross-sectional studies also suggested that sedentary lifestyle in hemodialysis patients could contribute to a higher BMI, and improving the lifestyle habits may help to decelerate aging [36,37].

Although our study was conducted in a multicenter and collected a large sample size contributed to the reliability of the experimental results, there were some limitations presented here. First, cross-sectional design cannot address causality. A single time-point measurement cannot represent the long-term status of patients. Future prospective cohort studies are needed to demonstrate a causal relationship between calcium-phosphorus metabolism and aging. Second, to determine the effect of the excluded samples on the results, external validity analyses were performed and showed some differences in age, dialysis vintage, residence areas, hypertension, use of medications, levels of calcium, phosphorus, and iPTH. Finally, there are differences in the calculating formula of biological age, and biological age obtained from blood biochemical indicators is susceptible to environmental, organismal status, and lifestyle effects, especially in hemodialysis patients, whose blood biochemical indicators have variability with the loss of renal function in patients. Therefore, the generalizability of our findings remains unknown.

5. Conclusion

This is the first study to analyze dialysis vintage, calcium, phosphorus and iPTH control and aging in hemodialysis patients. Patients with abnormal calcium, phosphorus and iPTH control and long-term hemodialysis are more likely to be at a higher risk of accelerated aging. These findings may provide empirical evidence that shorter dialysis vintage and maintaining normal calcium-phosphorus metabolism are benefit for delaying the process of aging in the hemodialysis population.

Funding Statement

The study was supported by Science Foundation of Anhui Medical University (2019xkj140); Clinical Research Incubation Program of The Second Hospital of Anhui Medical University (2020LCZD01); Co-construction project of clinical and preliminary disciplines of Anhui Medical University in 2020 (2020lcxk022).

Author contributions

Y.Z. wrote the main manuscript, and was responsible for formal analysis. H.Y., Z.Y. were responsible for data collection. X.L., Z.L., Y.B., G.Q., H.W., J.L., Y.G., S.Y., L.C., J.Y., J.H., S.M., J.Y., L.Y., R.S., X.J., H.W., F.Z., T.C., X.L., X.Z., L.L., J.F., W.W., Y.Z., G.S., were responsible for investigation. D.W. got the funding. S.T. was responsible for project administration and critical commentary or revision.

Disclosure statement

No potential conflict of interest was reported by the author(s).