Association between anorexia and hypoalbuminemia in the patients undergoing maintenance hemodialysis

Association between anorexia and hypoalbuminemia in the patients undergoing maintenance hemodialysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association between anorexia and hypoalbuminemia in the patients undergoing maintenance hemodialysis Zhen Yang, Xiaoting Qi, Yanlin Huang, Baolin Zou, Gaopeng Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2288603/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: Hypoalbuminemia is commonly observed in maintenance hemodialysis (MHD) patients and can serve as an important predictor of death in MHD patients. Anorexia is one of the important factors leading to hypoalbuminemia in MHD patients, so the purpose of this study was to examine the possible association between hypoalbuminemia and anorexia in MHD patients. Methods: Patients from three blood purification centers in Nanning, Guangxi, China, who met the inclusion criteria were selected. Anorexia was assessed by appetite assessment questionnaire. The presence of hypoalbuminemia was determined based on the level of serum albumin. Thereafter, an association between hypoalbuminemia and anorexia was analyzed using multiple logistics regression. Results: A total of 319 participants, age 54.80±15.41 (62.7% male), were included in the study. In this study,the prevalence of hypoalbuminemia was 22.3% (71) and the prevalence of anorexia was 34.2% (109). According to multiple logistics regression analysis, hypoalbuminemia and anorexia were independently correlated in Crude Model 1( OR :4.235 95% CI : 2.436 to 7.362 P ＜0.001) and Adjust Model ( OR :3.447 95% CI :1.654 to 7.185 P =0.001). In addition, age and symptom score were established as important risk factors for hypoalbuminemia( P ＜0.001); Body Mass Index (BMI), weekly dialysis frequency and serum total calcium (TCa) were identified as protective factors for hypoalbuminemia( P ＜0.001). Conclusions: Anorexia is an independent risk factor for the occurrence of hypoalbuminemia. In MHD patients, the incidence of anorexia and hypoalbuminemia can increase significantly with increasing age, and can lead to a significant decline in the quality of life. In the future, further studies are needed to further verify the relevant mechanisms between them, to provide reference for clinical intervention in MHD patients. Hypoalbuminemia Anorexia Maintenance hemodialysis Quality of life Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Serum albumin is an important nutritional marker and is routinely measured in MHD patients. As a result of protein-energy wasting (PEW) 's effect on nutrients, the influence of inflammatory factors and the filtering effect of hemodiafiltration (HDF) 1 – 4 , hypoalbuminemia is commonly observed in MHD patients. A series of studies have shown that serum albumin also serves an important factor for assessing malnutrition and predicting the survival of patients undergoing hemodialysis 5 – 7 . In hemodialysis patients, the risk of death was reported to increase by at least fivefold when serum albumin levels dropped to 30 to 35 g/L 8 . Therefore, strategies to mitigate the main contributing factors of hypoalbuminemia may be helpful in improving the overall survival rate of hemodialysis patients. Anorexia is defined as a loss of appetite and has been found to be present in about a third of hemodialysis patients 9 , A number of previous studies have shown the occurrence of anorexia in hemodialysis patients by altering the levels of circulating molecules known to regulate appetite like leptin, ghrelin, cholecystokinin, and neuropeptide Y 9 – 11 . Anorexia constitutes an important part in the evaluation of cachexia 12 . Its appearance may aggravate PEW in MHD patients, thereby resulting in hypoalbuminemia in MHD patients, and thereafter can accelerate the entry into the cachexia state. For most patients with end-stage renal disease, maintaining a good quality of life is the best pursuit because of the lack of kidney resources. A number of previous studies have shown that with an increasing age, the quality of life of MHD patients continues to decline 13 , and we infer that this may be related to the presence of anorexia and hypoalbuminemia. However, no studies so far have reported a direct association between anorexia and hypoalbuminemia. Therefore, the purpose of this study was to clarify whether hypoalbuminemia was indeed associated with anorexia in patients undergoing MHD and to analyze their changes in different age groups of patients. Materials And Methods Participants The patients with MHD in The Blood Purification Center from September 2019 to January 2020 were selected as the research objects. Inclusion criteria: (1) Age ≥ 18 and continuous hemodialysis ≥ 3 months; (2) Patients receiving hemodialysis treatment at least twice a week;(3) Independent reading and thinking ability, willing to cooperate, able to carry out normal language communication;(4) Having a clear consciousness, knowing his diagnosis and agreeing to participate in the study, signed the informed consent. Exclusion criteria: (1) there was cognitive impairment; (2) Recent organ transplantation or other major surgery;(3) Have low intelligence, mental problems or a history of mental disorders;(4) Concurrent tumor patients alive with other major diseases. A total of 319 hemodialysis patients were selected and included in the study. This study was reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University. Assessment Of Hypoalbuminemia We obtained the most recent serum albumin levels from the electronic records and then identified the patients with hypoalbuminemia based on the diagnostic criteria for hypoalbuminemia: serum albumin below 35g/L 14 . Assessment Of Anorexia In this study, SNAQ was selected as an anorexia assessment tool. SNAQ is widely used in the assessment of anorexia with high sensitivity and specificity, and its effectiveness has been confirmed in hemodialysis patients 15 , 16 . SNAQ includes four different items and adopts Likert-type five-point scoring system (very poor; poor; average; good; very good): The total score is added up, 4 points means the worst appetite, 20 points means the best appetite, score less than 14 points means that patient has anorexia, and lower the score, the more serious is the case of anorexia 17 . Sociodemographic Variables And Covariates We analyzed mainly the social demographic data including gender and age. Clinical characteristics such as dialysis age, weekly dialysis frequency, Body Mass Index(BMI), associated diseases (e.g. hypertension, diabetes, based on the latest diagnosis and test results to determine the presence of these diseases);Biochemical indicators: serum albumin, serum scratinine, intact parathyroid hormone(iPTH), serum phosphorus(Pi), serum potassium(K) and TCa. Additionally, quality of life indicators such as KDQOL-36 dimensions (SF-12 Physical Health Composite, SF-12 Mental Health Composite, Symptom/ Problem list, Effects of kidney disease, Burden of Kidney disease) were also evaluated. KDQOL-36 has been widely used to evaluate the quality of life of dialysis patients, and has been recognized in many clinical studies 18 – 20 . The validity of the Chinese version of KDQOL-36 has also been verified 21 , with good reliability and validity. The Cronbach coefficient of its subscale ranges from 0.810-0.931 22 .It consists of 36 items, 5 dimensions, including a short health survey of 12 items on the physical and mental dimensions, and 24 items on 3 specific disease subscales (list of symptoms/problems, impact of kidney disease, and burden of kidney disease) 23 , 24 . The raw data was converted using the KDQOL™-36 Scoring Program (V 2.0), and scores of each dimension were automatically presented. The higher the score, the better may be the quality of life as per the evidence available. Statistical analysis Epidata3.1 software was used for data input of two persons, and SPSS24.0 software was used for data analysis. All the patients were divided into hypoalbuminemia group and non- hypoalbuminemia group. Student’s t-test was used for measurement data, and χ2 was used for counting data. Multiple logistic regression models were then used to examine the association between anorexia and hypoalbuminemia, with hypoalbuminemia as the dependent variable. Three models, namely, Crude Model 1(univariate), Crude Model 2(univariate), Adjusted Model 2(adjusted for anorexia; BMI; age; weekly dialysis frequency; TCa; SF12-Mental; SF12-Physical; Symptom; Effects; Burden), were made. Receiver-operating characteristic (ROC) curve was used to analyze the value of SNAQ in predicting hypoalbuminemia in MHD patients. Pearson correlation analysis was used to explore the influence of age on each factor. All the results were found to be statistically significant with P < 0.05. Results Patient characteristics In Table 1, a total of 319 eligible participants, 200 males and 119 females, with an average age of 54.80±15.41 years, were included in this study. The prevalence of anorexia was observed to be around 34.2% and hypoalbuminemia 27.7%. All the patients were divided into hypoalbuminemia group and non- hypoalbuminemia group. Table 1 shows the demographic characteristics and scale scores for each group. We found that the prevalence rate of anorexia in hypoalbuminemia patients was 60.6%, higher than that in non- hypoalbuminemia patients (26.2%), and the difference was statistically significant ( P < 0.05). Thereafter, based on the comparison between the two groups, we also observed that there were significant differences in average age, BMI, weekly dialysis frequency, Ca, anorexia, SF-12 Physical Health Composite, SF-12 Mental Health Composite, Symptom/ Problem list, effects of kidney disease and burden of Kidney disease ( P < 0.05). Association of hypoalbuminemia with anorexia In Table 2, multiple logistic regression analysis showed the association between anorexia and hypoalbuminemia in MHD patients. The Crude Model 1 clearly indicated that anorexia of ageing had significantly independent association with hypoalbuminemia ( OR : 4.235,95% CI : 2.436 to 7.362, P < 0.001). In Adjusted Model, anorexia and hypoalbuminemia remained significantly independent ( OR : 3.447,95% CI : 1.654 to 7.185, P =0.001). In Figure 1, The Area Under Curve(AUC) of SNAQ for predicting hypoalbuminemia was 0.728( P < 0.001). Significant factors involved in the development of hypoalbuminemia In Crude Model 2, age was an independent risk factor for hypoalbuminemia ( OR : 1.029,95% CI : 1.010 to 1.048, P =0.002). The Adjusted Model showed that age ( OR : 1.026,95% CI : 1.003 to 1.049, P =0.029) and symptom ( OR : 1.040,95% CI : 1.006 to 1.076, P =0.040) were independent risk factors for hypoalbuminemia except for anorexia. BMI ( OR : 0.861,95% CI : 0.784 to 0.946, P =0.002), weekly dialysis frequency ( OR : 0.311,95% CI : 0.158 to 0.611, P =0.001) and TCa ( OR : 0.240,95% CI : 0.078 to 0.733, P =0.012) were protective factors for hypoalbuminemia. Changes of hypoalbuminemia and anorexia in MHD patients of different ages In Figure 2, the prevalence of anorexia in ≥ 60 years old group (43.8%) was significantly higher than that in the young and 18≤ years old＜60 group (26.9%). In Figure 3, the prevalence of hypoalbuminemia in ≥ 60 years old group (27.5) was significantly higher than that in the young and 18≤ years old＜60 group(20.7%). In Table 2, both Crude Model 2 and the Adjusted Model groups showed that age was an independent risk factor for hypoalbuminemia. In Figure 4, age was negatively correlated with serum albumin and SNAQ. In addition, with an increase of age, the KDQOL-36 questionnaire was negatively correlated with other dimensions except for SF12-mental. Discussion This study mainly provided evidence that hypoalbuminemia could be closely related to anorexia, and the incidence of both changes with age, thereby further clarifying the relationship between anorexia, albumin level and age. The incidence of hypoalbuminemia and anorexia increases with age, along with a decline in quality of life, thus leading to a cachexia state and increased mortality for MHD. In the future, optimal interventions should be developed to improve the nutritional status of MHD patients. This study also found that the incidence rate of MHD anorexia was 34.2%, which was consistent with the previous findings on anorexia in MHD patients 9 . The incidence rate of anorexia in elderly patients ≥ 60 years old was 60.6%, which was much higher than that in young and middle-aged MHD people (18≤years old＜60), and far higher than the Japanese scholar for the community elderly population of the survey results 25 . Anorexia in the elderly population has always been an important research field, the causes of which mainly include sensory degeneration, gastric emptied disorders and so on 26,27 . Anorexia is a commonly found condition in MHD population. A number of previous studies have found that inadequate dialysis is one of the main reasons for the decreased appetite of MHD patients 28 . It has been reported that because of the characteristics of their own diseases, MHD patients will often experience toxin retention. In this study, we found that weekly dialysis frequency was a protective factor for hypoalbuminemia, thereby maintaining a high frequency of dialysis could significantly improve the efficiency of removing toxins in MHD patients, as well as the patient's appetite, and thus indirectly enhance the nutritional status of MHD patients. However, some studies have found that dialysis can lead to a significant decrease of ghrelin in patients 29 . Ghrelin is an orexin released by gastric endocrine cells, which can effectively increase appetite and regulate energy balance 30 . The decrease of ghrelin can lead to the decrease of appetite, which may be due to the influence of dialysate, which needs further analysis in the future. In addition, leptin and cholecystokinin (CCK) levels have been found to be significantly higher than normal in patients with uremia due to renal retention or excessive secretion of leptin and CCK 10,11 . CCK is a satiety factor, which can inhibit gastric emptying and produce satiety 31 .Leptin induces appetite suppression by decreasing the level of hypothalamic neuropeptide Y (NPY), which has an appetite-promoting effect 32 . Therefore, the incidence of anorexia in MHD group at all ages is was significantly higher than that in the general community population. Both anorexia and albumin levels constitute an important part of the evaluation of cachexia, and previous studies have found that PEW/cachexia is often associated with hypoalbuminemia and decreased appetite 33,34 . In this study, we found that anorexia is an independent risk factor for hypoalbuminemia, thus further supporting our hypothesis. At the same time, the occurrence of hypoalbuminemia was also closely related to age, as shown in Table 2. Both Crude Model 2 and Adjusted Model indicated that age was an independent risk factor for the occurrence of hypoalbuminemia. In Figure 4, it was found that both serum proteinemia and SNAQ scores were negatively correlated with age. In Figure 3, we also demonstrated that the incidence of hypoalbuminemia in patients ≥60 years old was significantly higher than that in young and middle-aged patients aged 18 to 59 years old, which is consistent with the findings of previous studies 35 . In this study, the incidence of hypoalbuminemia in MHD patients was 22.3%, which contributed to the numerous reasons for hypoalbuminemia in MHD patients. In Table 2, we show that in addition to anorexia and age, BMI, weekly dialysis frequency, serum calcium and symptom scores were significant influencing factors for hypoalbuminemia, among which BMI, weekly dialysis frequency and serum calcium were protective factors. BMI is a nutritional index, and a higher BMI indicates a better nutritional status of the patient. It can be inferred that dialysis frequency can improve dialysis adequacy, thereby indirectly improving appetite and nutritional status of MHD patients. Hypocalcemia is relatively common condition in MHD patients. A few studies have found that for most patients, hypocalcemia can lead to a state of hypoalbuminemia, which is consistent with the results of this study 36 . In the Adjusted Model, symptom score is an independent risk factor for hypoalbuminemia, and symptom score can act as an important part of the quality of life assessment of MHD patients. It is not difficult to understand that the nutritional status of MHD patients is closely related to their quality of life. In Table 1, we show that the scores of all the dimensions of the KDQOL-36 scale in patients with hypoalbuminemia were significantly lower than those in the non-hypoalbuminemia group. Therefore, hypoalbuminemia may lead to a decreased quality of life in patients, which is consistent with the findings of previous related studies 37 . In Figure 4, with an increase of age, serum albumin level, SNAQ score and all dimensions of KDQOL-36 except SF-12mental dimension were found to be negatively correlated. Therefore, based on the above observations the potential relationship between age and hypoalbuminemia, anorexia and quality of life can be clearly inferred that is, an increase of age will cause the decrease of appetite and serum albumin levels, which will lead to the occurrence of cachexia, adversely affect the quality of life in MHD patients and thus increase their mortality. As a common appetite assessment tool, SNAQ has found good applicability in clinical practice. In many poor areas, MHD blood collection cannot be carried out frequently due to lack of adequate economic and medical facilities. However, compared with SNAQ, blood collection can be conveniently implemented in the clinical practice. The cutoff point for SNAQ indicating the occurrence of anorexia during ageing has been found to be 4.235 times greater OR of hypoalbuminemia. In Figure 1, we found that the ROC of SNAQ in the diagnosis of hypoalbuminemia was 0.728, 95% CI(0.666-0.790), and its sensitivity was acceptable. The advantage of this study is that it enables us to further clarify and confirm the potential relationship between anorexia and hypoalbuminemia in MHD patients, and to evaluate possible influencing factors of hypoalbuminemia. Nevertheless, there were several limitations associated with the the present study. First, this study is a cross-sectional study, hence unable to completely understand the impact of dynamic changes in albumin on anorexia development in MHD patients. Second, this study only investigated 319 effective samples from three blood purification centers, and the sample size should be increased for further analysis in the future. Third, due to the lack of some data in the blood purification center, this study did not distinguish between different HDF patients, and so it was impossible to explore the effect of HDF on the serum albumin levels. Finally, many studies have shown that hypoproteinemia and anorexia can also be closely associated with some laboratory indicators (e.g., NPY, IL6, cholecystokinin, ghrelin, leptin, etc.) 10,11,32,38-41 but we were unable to explore these indicators further due to the current lack of availability of appropriate resources. In conclusion, hypoalbuminemia and anorexia are common and closely related in MHD patients. With an increase of age, the incidence of hypoalbuminemia and anorexia will increase, and the quality of life of MHD patients will decrease. Therefore, preventing low BMI and serum total calcium and increasing dialysis frequency could significantly reduce the incidence of hypoalbuminemia. In the future, we aim to develop targeted intervention programs to reduce the incidence of both anorexia and hypoalbuminemia by modifying the relevant influencing factors to significantly improve the overall quality of life of MHD patients. The practical applications This study mainly investigated the relationship between hypoalbuminemia and anorexia in maintenance hemodialysis patients, and analyzed the influence of age on both and quality of life. It can provide new ideas and data support for the study of nutritional intervention in MHD patients. Declarations Ethics approval and consent to participate Our study complied with the principles of the Declaration of Helsinki and was approved by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University., Nanning, Guangxi. We obtained written informed consent from all participants enrolled. Consent for publication Not applicable. Competing interests The authors declare that they have no conflict of interest. Acknowledgements The authors thank all volunteers who participated in this study. Authors’ contributions ZY designed the study. XTQ conducted study and wrote the manuscript. XTQ and BLZ ※ collected the data. 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Curr Med Res Opin . 1976;4(2):101-16 Guney I, Atalay H, Solak Y et al. Poor quality of life is associated with increased mortality in maintenance hemodialysis patients: a prospective cohort study. Saudi J Kidney Dis Transpl . 2012;23(3):493-9 Grunfeld C, Zhao C, Fuller J et al. Endotoxin and cytokines induce expression of leptin, the ob gene product, in hamsters. J Clin Invest . 1996;97(9):2152-7 Kalantar-Zadeh K, Block G, McAllister CJ, Humphreys MH, Kopple JD. Appetite and inflammation, nutrition, anemia, and clinical outcome in hemodialysis patients. Am J Clin Nutr . 2004;80(2):299-307 Nusken KD, Groschl M, Rauh M et al. Effect of renal failure and dialysis on circulating ghrelin concentration in children. Nephrol Dial Transplant . 2004;19(8):2156-7 Montazerifar F, Karajibani M, Gorgij F, Akbari O. Malnutrition Markers and Serum Ghrelin Levels in Hemodialysis Patients. Int Sch Res Notices . 2014;2014:765895 Tables Table 1 Comparison of general and clinical data between hypoalbuminemia group and no- hypoalbuminemia group Items Overall cohort N=319 No- hypoalbuminemia N=248(77.7%) hypoalbuminemia N=71(22.3%) χ 2/t P Age, years ± SD 54.80±15.41 53.36±15.30 59.82±14.82 -3.157 ＜0.001 Male, number (%) 200(62.7) 159(64.1) 41(57.7) 0.224 0.636 Dialysis age, months± SD 45.8±39.0 47.96±38.96 38.07±38.51 1.891 0.060 Weekly dialysis frequency, number ± SD 2.70±0.43 2.75±0.39 2.49±0.48 4.668 ＜0.001 BMI, kg/㎡ ± SD 22.25±3.68 22.54±3.73 21.24±3.34 2.656 0.008 Serum scratinine, umoI/L 102.12±21.17 893.41±312.16 943.18±318.10 -1.180 0.239 iPTH, pg/ml 495.47±404.05 488.78±398.23 518.84±425.88 -0.552 0.581 Pi, mmol/L ± SD 1.81±0.65 1.79±0.66 1.88±0.59 -1.065 0.288 K, mmol/L ± SD 4.73±0.73 4.65±0.70 4.88±0.77 -1.563 0.119 TCa, mmol/L ± SD 2.21±0.29 2.24±0.29 2.11±0.28 3.478 0.001 Anorexia, number (%) 109(34.2) 66(26.6) 43(60.6) 12.289 ＜0.001 Diabetes, number (%) 49(15.4) 38(15.3) 11(15.5) 0.001 0.976 SF12-Mental± SD 36.58±5.66 36.92±5.58 35.37±5.79 2.051 0.041 SF12-Physical± SD 34.69±6.42 35.50±6.38 31.85±5.74 4.338 ＜0.001 Symptom± SD 72.17±12.12 73.00±12.14 69.25±11.64 2.316 0.021 Effects± SD 51.63±11.99 52.88±11.20 47.28±13.61 3.170 0.002 Burden± SD 14.97±13.72 16.15±13.75 10.83±12.85 2.919 0.004 BMI, Body Mass Index; iPTH, intact parathyroid hormone; SF12-Mental, SF-12 Mental Health Composite; SF12-Physical, SF-12 Physical Health Composite; SD, standard deviation; TCa, Serum total calcium; K, Serum Potassium; Pi, Serum phosphorus Table 2 Association between anorexia and hypoalbuminemia on multiple logistic regression models B SE Waldχ2 P OR 95%CI Crude Model 1 Anorexia 1.443 0.282 26.166 ＜0.001 4.235 2.436-7.362 Crude Model 2 Age 0.029 0.009 9.424 0.002 1.029 1.010-1.048 Adjusted Model Anorexia 1.238 0.375 10.904 0.001 3.447 1.654-7.185 BMI -0.150 0.048 9.678 0.002 0.861 0.784-0.946 Age 0.025 0.012 4.782 0.029 1.026 1.003-1.049 Weekly dialysis frequency -1.168 0.344 11.499 0.001 0.311 0.158-0.611 TCa -1.429 0.571 6.265 0.012 0.240 0.078-0.733 SF12-Mental -0.050 0.035 2.102 0.147 0.951 0.888-1.018 SF12-Physical -0.039 0.033 1.363 0.243 0.962 0.902-1.027 Symptom 0.040 0.017 5.259 0.022 1.040 1.006-1.076 Effects -0.022 0.018 1.484 0.223 0.979 0.945-1.013 Burden 0.009 0.016 0.311 0.577 1.009 0.977-1.042 Crude model 1(univariate), Crude model 2(univariate), Adjusted model 2(adjusted for anorexia; BMI; age; weekly dialysis frequency; TCa; SF12-Mental; SF12-Physical; Symptom; Effects; Burden). B , coefficient value; SE , standard error; OR , odds ratio; CI , confidence interval Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2288603","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":160169227,"identity":"c72c9a3a-0395-4274-9093-c57ea977d951","order_by":0,"name":"Zhen Yang","email":"","orcid":"","institution":"Department of Nursing, Henan Provincial People's Hospital, Department of Nursing of Central China Fuwai Hospital, Central China Fuwai Hosptal of Zhengzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zhen","middleName":"","lastName":"Yang","suffix":""},{"id":160169230,"identity":"8b2f2e2a-fb7b-4394-8c72-acf924e0ecb5","order_by":1,"name":"Xiaoting Qi","email":"","orcid":"","institution":"Department of Nursing, Henan Provincial People's Hospital, Department of Nursing of Central China Fuwai Hospital, Central China Fuwai Hosptal of Zhengzhou University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaoting","middleName":"","lastName":"Qi","suffix":""},{"id":160169232,"identity":"b2b0911b-dbc5-4553-8b7d-28f653893db4","order_by":2,"name":"Yanlin Huang","email":"","orcid":"","institution":"First Affiliated Hospital of GuangXi Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yanlin","middleName":"","lastName":"Huang","suffix":""},{"id":160169234,"identity":"fcb8f445-5b09-4673-98fa-3d73df9899ca","order_by":3,"name":"Baolin Zou","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxUlEQVRIiWNgGAWjYBACNvnDB4z/VNjwMLY3EKmFT4ItoYDnTJocc88BIrXISfAofOBtO2zMPiOBWIdJ9zBukDiTltg78/HGGww1NtGEtcicPWxgUGGTOHN2WrEFw7G03AaCWhjy0gwSgLZsnJ1jJsHYcJgYLTnmPw62HU7cf/MMsVokcgwMG4HeZ5zBQ6wWnmMJxgzAQGbsAfolgRi/yLc3HzBmAEfl4Y03PtTYENaCDAwkEkhRDtFCqo5RMApGwSgYGQAAlp1Biq4K440AAAAASUVORK5CYII=","orcid":"","institution":"First Affiliated Hospital of GuangXi Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Baolin","middleName":"","lastName":"Zou","suffix":""},{"id":160169236,"identity":"d1299695-db23-46af-9f28-ab4c5c2f55fd","order_by":4,"name":"Gaopeng Li","email":"","orcid":"","institution":"Department of cardiovascular Physiology Faculty of Medicine,Kagawa University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Gaopeng","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2022-11-18 13:59:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2288603/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2288603/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":30533577,"identity":"e327c931-44ea-4654-9ebc-7481c2adf33c","added_by":"auto","created_at":"2022-12-19 19:39:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":41571,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve of SNAQ for prediction of hypoalbuminemia(AUC=0.728,\u003cem\u003eP\u003c/em\u003e＜0.001)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-2288603/v1/117135209c0f2215d33b10c8.png"},{"id":30533893,"identity":"0f39e8aa-69f5-4b15-a866-deeb72e23546","added_by":"auto","created_at":"2022-12-19 19:47:37","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":19028,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of anorexia among MHD patients according to the age group.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-2288603/v1/becb44c59f5dfbc9ad91bc97.png"},{"id":30533578,"identity":"86d92166-6e39-4abe-8555-3a91cf1fd5f2","added_by":"auto","created_at":"2022-12-19 19:39:37","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":18640,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of hypoproteinemia among MHD patients according to the age group.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-2288603/v1/d32eb6851409b2a1e9b95ae3.png"},{"id":30533580,"identity":"8c934f72-da45-4e32-a363-14fbeefb3661","added_by":"auto","created_at":"2022-12-19 19:39:37","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":90376,"visible":true,"origin":"","legend":"\u003cp\u003ePearson correlation analysis hotspot map of age and factors.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-2288603/v1/e85c586814e027a280d98972.png"},{"id":31345771,"identity":"0335f928-31ab-418a-8cee-b4b15c1d699c","added_by":"auto","created_at":"2023-01-10 06:29:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":535571,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2288603/v1/9b98d23e-9962-4bbd-bf2a-294c9fa5c2be.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association between anorexia and hypoalbuminemia in the patients undergoing maintenance hemodialysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSerum albumin is an important nutritional marker and is routinely measured in MHD patients. As a result of protein-energy wasting (PEW) 's effect on nutrients, the influence of inflammatory factors and the filtering effect of hemodiafiltration (HDF)\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, hypoalbuminemia is commonly observed in MHD patients. A series of studies have shown that serum albumin also serves an important factor for assessing malnutrition and predicting the survival of patients undergoing hemodialysis\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. In hemodialysis patients, the risk of death was reported to increase by at least fivefold when serum albumin levels dropped to 30 to 35 g/L\u003csup\u003e8\u003c/sup\u003e. Therefore, strategies to mitigate the main contributing factors of hypoalbuminemia may be helpful in improving the overall survival rate of hemodialysis patients.\u003c/p\u003e \u003cp\u003eAnorexia is defined as a loss of appetite and has been found to be present in about a third of hemodialysis patients\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e, A number of previous studies have shown the occurrence of anorexia in hemodialysis patients by altering the levels of circulating molecules known to regulate appetite like leptin, ghrelin, cholecystokinin, and neuropeptide Y\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Anorexia constitutes an important part in the evaluation of cachexia\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Its appearance may aggravate PEW in MHD patients, thereby resulting in hypoalbuminemia in MHD patients, and thereafter can accelerate the entry into the cachexia state. For most patients with end-stage renal disease, maintaining a good quality of life is the best pursuit because of the lack of kidney resources. A number of previous studies have shown that with an increasing age, the quality of life of MHD patients continues to decline\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, and we infer that this may be related to the presence of anorexia and hypoalbuminemia.\u003c/p\u003e \u003cp\u003eHowever, no studies so far have reported a direct association between anorexia and hypoalbuminemia. Therefore, the purpose of this study was to clarify whether hypoalbuminemia was indeed associated with anorexia in patients undergoing MHD and to analyze their changes in different age groups of patients.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe patients with MHD in The Blood Purification Center from September 2019 to January 2020 were selected as the research objects. Inclusion criteria: (1) Age\u0026thinsp;\u0026ge;\u0026thinsp;18 and continuous hemodialysis\u0026thinsp;\u0026ge;\u0026thinsp;3 months; (2) Patients receiving hemodialysis treatment at least twice a week;(3) Independent reading and thinking ability, willing to cooperate, able to carry out normal language communication;(4) Having a clear consciousness, knowing his diagnosis and agreeing to participate in the study, signed the informed consent. Exclusion criteria: (1) there was cognitive impairment; (2) Recent organ transplantation or other major surgery;(3) Have low intelligence, mental problems or a history of mental disorders;(4) Concurrent tumor patients alive with other major diseases.\u003c/p\u003e \u003cp\u003eA total of 319 hemodialysis patients were selected and included in the study. This study was reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssessment Of Hypoalbuminemia\u003c/h3\u003e\n\u003cp\u003eWe obtained the most recent serum albumin levels from the electronic records and then identified the patients with hypoalbuminemia based on the diagnostic criteria for hypoalbuminemia: serum albumin below 35g/L\u003csup\u003e14\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eAssessment Of Anorexia\u003c/h3\u003e\n\u003cp\u003eIn this study, SNAQ was selected as an anorexia assessment tool. SNAQ is widely used in the assessment of anorexia with high sensitivity and specificity, and its effectiveness has been confirmed in hemodialysis patients\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. SNAQ includes four different items and adopts Likert-type five-point scoring system (very poor; poor; average; good; very good): The total score is added up, 4 points means the worst appetite, 20 points means the best appetite, score less than 14 points means that patient has anorexia, and lower the score, the more serious is the case of anorexia\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eSociodemographic Variables And Covariates\u003c/h3\u003e\n\u003cp\u003eWe analyzed mainly the social demographic data including gender and age. Clinical characteristics such as dialysis age, weekly dialysis frequency, Body Mass Index(BMI), associated diseases (e.g. hypertension, diabetes, based on the latest diagnosis and test results to determine the presence of these diseases);Biochemical indicators: serum albumin, serum scratinine, intact parathyroid hormone(iPTH), serum phosphorus(Pi), serum potassium(K) and TCa. Additionally, quality of life indicators such as KDQOL-36 dimensions (SF-12 Physical Health Composite, SF-12 Mental Health Composite, Symptom/ Problem list, Effects of kidney disease, Burden of Kidney disease) were also evaluated.\u003c/p\u003e \u003cp\u003eKDQOL-36 has been widely used to evaluate the quality of life of dialysis patients, and has been recognized in many clinical studies\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The validity of the Chinese version of KDQOL-36 has also been verified\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, with good reliability and validity. The Cronbach coefficient of its subscale ranges from 0.810-0.931\u003csup\u003e22\u003c/sup\u003e.It consists of 36 items, 5 dimensions, including a short health survey of 12 items on the physical and mental dimensions, and 24 items on 3 specific disease subscales (list of symptoms/problems, impact of kidney disease, and burden of kidney disease)\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The raw data was converted using the KDQOL\u0026trade;-36 Scoring Program (V 2.0), and scores of each dimension were automatically presented. The higher the score, the better may be the quality of life as per the evidence available.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eEpidata3.1 software was used for data input of two persons, and SPSS24.0 software was used for data analysis. All the patients were divided into hypoalbuminemia group and non- hypoalbuminemia group. Student\u0026rsquo;s t-test was used for measurement data, and χ2 was used for counting data. Multiple logistic regression models were then used to examine the association between anorexia and hypoalbuminemia, with hypoalbuminemia as the dependent variable. Three models, namely, Crude Model 1(univariate), Crude Model 2(univariate), Adjusted Model 2(adjusted for anorexia; BMI; age; weekly dialysis frequency; TCa; SF12-Mental; SF12-Physical; Symptom; Effects; Burden), were made. Receiver-operating characteristic (ROC) curve was used to analyze the value of SNAQ in predicting hypoalbuminemia in MHD patients. Pearson correlation analysis was used to explore the influence of age on each factor. All the results were found to be statistically significant with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003ePatient characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn Table 1, a total of 319 eligible participants, 200 males and 119 females, with an average age of 54.80\u0026plusmn;15.41 years, were included in this study. The prevalence of anorexia was observed to be around 34.2% and hypoalbuminemia 27.7%. All the patients were divided into\u0026nbsp;hypoalbuminemia\u0026nbsp;group and non-\u0026nbsp;hypoalbuminemia\u0026nbsp;group. Table 1 shows the demographic characteristics and scale scores for each group. We found that the prevalence rate of\u0026nbsp;anorexia in\u0026nbsp;hypoalbuminemia patients was 60.6%, higher than that in non-\u0026nbsp;hypoalbuminemia\u0026nbsp;patients (26.2%), and the difference was statistically significant (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Thereafter, based on the comparison between the two groups, we also observed that there were significant differences in average age,\u0026nbsp;BMI, weekly dialysis frequency, Ca, anorexia,\u0026nbsp;SF-12 Physical Health Composite, SF-12 Mental Health Composite, Symptom/ Problem list, effects of kidney disease and burden of Kidney disease\u0026nbsp;(\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAssociation of hypoalbuminemia with anorexia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn Table 2, multiple logistic regression analysis showed the association between anorexia and hypoalbuminemia in MHD patients.\u0026nbsp;The Crude Model 1 clearly indicated that anorexia of ageing had significantly independent association with hypoalbuminemia (\u003cem\u003eOR\u003c/em\u003e: 4.235,95% \u003cem\u003eCI\u003c/em\u003e: 2.436 to 7.362, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). In\u0026nbsp;Adjusted Model,\u0026nbsp;anorexia and hypoalbuminemia remained significantly independent (\u003cem\u003eOR\u003c/em\u003e: 3.447,95%\u003cem\u003e\u0026nbsp;CI\u003c/em\u003e: 1.654 to 7.185,\u003cem\u003e\u0026nbsp;P\u003c/em\u003e=0.001).\u0026nbsp;In Figure 1, The Area Under Curve(AUC) of SNAQ for predicting hypoalbuminemia was\u0026nbsp;0.728(\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSignificant factors\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;involved\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;in the development of hypoalbuminemia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn Crude Model 2, age was an independent risk factor for hypoalbuminemia\u0026nbsp;(\u003cem\u003eOR\u003c/em\u003e: 1.029,95% \u003cem\u003eCI\u003c/em\u003e: 1.010 to 1.048, \u003cem\u003eP\u003c/em\u003e=0.002). The Adjusted Model showed that age\u0026nbsp;(\u003cem\u003eOR\u003c/em\u003e: 1.026,95% \u003cem\u003eCI\u003c/em\u003e: 1.003 to 1.049, \u003cem\u003eP\u003c/em\u003e=0.029) and symptom\u0026nbsp;(\u003cem\u003eOR\u003c/em\u003e: 1.040,95% \u003cem\u003eCI\u003c/em\u003e: 1.006 to 1.076, \u003cem\u003eP\u003c/em\u003e=0.040)\u0026nbsp;were independent risk factors for hypoalbuminemia except for anorexia. BMI\u0026nbsp;(\u003cem\u003eOR\u003c/em\u003e: 0.861,95% \u003cem\u003eCI\u003c/em\u003e: 0.784 to 0.946, \u003cem\u003eP\u003c/em\u003e=0.002), weekly dialysis frequency\u0026nbsp;(\u003cem\u003eOR\u003c/em\u003e: 0.311,95% \u003cem\u003eCI\u003c/em\u003e: 0.158 to 0.611, \u003cem\u003eP\u003c/em\u003e=0.001)\u0026nbsp;and TCa\u0026nbsp;(\u003cem\u003eOR\u003c/em\u003e: 0.240,95% \u003cem\u003eCI\u003c/em\u003e: 0.078 to 0.733, \u003cem\u003eP\u003c/em\u003e=0.012)\u0026nbsp;were protective factors for hypoalbuminemia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChanges of hypoalbuminemia and anorexia in MHD patients of different ages\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn Figure 2, the prevalence of anorexia in \u0026ge; 60 years old group (43.8%) was significantly higher than that in the young and 18\u0026le; years old＜60 group (26.9%). In Figure 3, the prevalence of hypoalbuminemia in \u0026ge; 60 years old group (27.5) was significantly higher than that in the young and 18\u0026le; years old＜60 group(20.7%). In Table 2, both Crude Model 2 and the Adjusted Model groups showed that age was an independent risk factor for hypoalbuminemia. In Figure 4, age was negatively correlated with serum albumin and SNAQ. In addition, with an increase of age, the KDQOL-36 questionnaire was negatively correlated with other dimensions except for SF12-mental.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study mainly\u0026nbsp;provided evidence\u0026nbsp;that hypoalbuminemia\u0026nbsp;could be\u0026nbsp;closely related to anorexia, and the incidence of both changes with age,\u0026nbsp;thereby\u0026nbsp;further clarifying the relationship between anorexia, albumin level and age. The incidence of hypoalbuminemia and anorexia increases with age, along with a decline in quality of life,\u0026nbsp;thus\u0026nbsp;leading to a cachexia state and increased mortality for MHD. In the future,\u0026nbsp;optimal\u0026nbsp;interventions should be developed to improve the nutritional status of MHD patients.\u003c/p\u003e\n\u003cp\u003eThis study\u0026nbsp;also\u0026nbsp;found that the incidence rate of MHD anorexia was 34.2%, which was consistent with the previous findings on anorexia in MHD patients\u003csup\u003e9\u003c/sup\u003e. The incidence rate of anorexia in elderly patients\u0026nbsp;\u0026ge;\u0026nbsp;60 years old was 60.6%, which was much higher than that in young and middle-aged MHD people\u0026nbsp;(18\u0026le;years old＜60), and far higher than the Japanese scholar for the community elderly population of the survey results\u003csup\u003e25\u003c/sup\u003e.\u0026nbsp;Anorexia in the elderly population has always been\u0026nbsp;an important\u0026nbsp;research field, the causes of which mainly include sensory degeneration, gastric emptied disorders and so on\u003csup\u003e26,27\u003c/sup\u003e. Anorexia is a\u0026nbsp;commonly found\u0026nbsp;condition in MHD population.\u0026nbsp;A number of previous\u0026nbsp;studies have found that inadequate dialysis is one of the main reasons for\u0026nbsp;the\u0026nbsp;decreased appetite of MHD patients\u003csup\u003e28\u003c/sup\u003e.\u0026nbsp;It has been reported that because of\u0026nbsp;the characteristics of their own diseases, MHD patients will often experience toxin retention. In this study, we found that weekly dialysis frequency was a protective factor for hypoalbuminemia,\u0026nbsp;thereby\u0026nbsp;maintaining a high frequency of dialysis could\u0026nbsp;significantly\u0026nbsp;improve the efficiency of removing toxins in MHD patients,\u0026nbsp;as well as\u0026nbsp;the patient\u0026apos;s appetite, and thus indirectly\u0026nbsp;enhance\u0026nbsp;the nutritional status of MHD patients. However, some studies have found that dialysis can lead to\u0026nbsp;a significant\u0026nbsp;decrease of ghrelin in patients\u003csup\u003e29\u003c/sup\u003e. Ghrelin is an orexin released by gastric endocrine cells, which can\u0026nbsp;effectively\u0026nbsp;increase appetite and regulate energy balance\u003csup\u003e30\u003c/sup\u003e. The decrease of ghrelin can lead to the decrease of appetite, which may be due to the influence of dialysate, which needs further\u0026nbsp;analysis\u0026nbsp;in the future. In addition, leptin and cholecystokinin (CCK) levels\u0026nbsp;have been found to be significantly\u0026nbsp;higher than normal in patients with uremia due to renal retention or excessive secretion of leptin and CCK\u003csup\u003e10,11\u003c/sup\u003e.\u0026nbsp;CCK is a satiety factor, which can inhibit gastric emptying and produce satiety\u003csup\u003e31\u003c/sup\u003e.Leptin induces appetite suppression by decreasing the level of hypothalamic neuropeptide Y (NPY), which has an appetite-promoting effect\u003csup\u003e32\u003c/sup\u003e. Therefore, the incidence of anorexia in MHD group at all ages is\u0026nbsp;was significantly\u0026nbsp;higher than that in the general community population.\u003c/p\u003e\n\u003cp\u003eBoth anorexia and albumin levels\u0026nbsp;constitute\u0026nbsp;an important part of the evaluation of cachexia, and previous studies have found that PEW/cachexia is often associated with hypoalbuminemia and decreased appetite\u003csup\u003e33,34\u003c/sup\u003e. In this study, we found that anorexia is an independent risk factor for hypoalbuminemia,\u0026nbsp;thus\u0026nbsp;further supporting our hypothesis. At the same time, the occurrence of hypoalbuminemia was also closely related to age, as shown in Table 2. Both Crude Model 2 and Adjusted Model indicated that age was an independent risk factor for the occurrence of hypoalbuminemia. In Figure 4,\u0026nbsp;it was\u0026nbsp;found that both serum proteinemia and SNAQ scores were negatively correlated with age. In Figure 3, we also\u0026nbsp;demonstrated\u0026nbsp;that the incidence of hypoalbuminemia in patients\u0026nbsp;\u0026ge;60 years old\u0026nbsp;was\u0026nbsp;significantly higher than that in young and middle-aged patients aged 18 to 59 years old, which is consistent with the findings of previous studies\u0026nbsp;\u003csup\u003e35\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn this study, the incidence of hypoalbuminemia in MHD patients was 22.3%, which\u0026nbsp;contributed to the\u0026nbsp;numerous reasons for hypoalbuminemia in MHD patients. In Table 2, we\u0026nbsp;show\u0026nbsp;that in addition to anorexia and age, BMI, weekly dialysis frequency, serum calcium and symptom scores were significant influencing factors for hypoalbuminemia, among which BMI, weekly dialysis frequency and serum calcium were protective factors. BMI is a nutritional index, and a higher BMI indicates a better nutritional status of the patient. It can be inferred that dialysis frequency can improve dialysis adequacy, thereby indirectly improving appetite and nutritional status of MHD patients. Hypocalcemia is relatively common\u0026nbsp;condition\u0026nbsp;in MHD patients.\u0026nbsp;A few studies\u0026nbsp;\u0026nbsp;have found that for most patients, hypocalcemia can lead to a state of hypoalbuminemia, which is consistent with the results of this study\u003csup\u003e36\u003c/sup\u003e. In the Adjusted Model, symptom score is an independent risk factor for hypoalbuminemia, and symptom score\u0026nbsp;can act as\u0026nbsp;an important part of the quality of life assessment of MHD patients. It is not difficult to understand that the nutritional status of MHD patients is closely related to their quality of life. In Table 1, we\u0026nbsp;show\u0026nbsp;that the scores of all\u0026nbsp;the\u0026nbsp;dimensions of the KDQOL-36 scale in patients with hypoalbuminemia were significantly lower than those in the non-hypoalbuminemia group. Therefore, hypoalbuminemia may lead to\u0026nbsp;a\u0026nbsp;decreased quality of life in patients, which is consistent with\u0026nbsp;the findings of\u0026nbsp;previous related studies\u003csup\u003e37\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn Figure 4, with\u0026nbsp;an\u0026nbsp;increase of age, serum albumin level, SNAQ score and all dimensions of KDQOL-36 except SF-12mental dimension were\u0026nbsp;found to be\u0026nbsp;negatively correlated.\u0026nbsp;Therefore, based on\u0026nbsp;the above\u0026nbsp;observations\u0026nbsp;the\u0026nbsp;potential\u0026nbsp;relationship between age and hypoalbuminemia, anorexia and quality of life\u0026nbsp;can be clearly inferred\u0026nbsp;that is,\u0026nbsp;an\u0026nbsp;increase of age will cause the decrease of appetite and serum albumin levels, which will lead to the occurrence of cachexia, adversely\u0026nbsp;affect the quality of life in MHD patients and\u0026nbsp;thus\u0026nbsp;increase their mortality.\u003c/p\u003e\n\u003cp\u003eAs a common appetite assessment tool, SNAQ has\u0026nbsp;found\u0026nbsp;good applicability in clinical practice.\u0026nbsp;In many poor areas, MHD blood collection cannot be carried out frequently due to lack of adequate economic and medical facilities. However, compared with SNAQ, blood collection can be conveniently implemented in the clinical practice. The cutoff point for SNAQ indicating the occurrence of anorexia during ageing has been found to be 4.235 times greater OR of hypoalbuminemia.\u0026nbsp;In Figure 1, we found that the ROC of SNAQ in the diagnosis of hypoalbuminemia was 0.728, 95% CI(0.666-0.790), and its sensitivity was acceptable.\u003c/p\u003e\n\u003cp\u003eThe advantage of this study is that it enables us to further clarify and confirm the potential relationship between anorexia and hypoalbuminemia in\u0026nbsp;MHD patients, and\u0026nbsp;to evaluate\u0026nbsp;possible influencing factors of hypoalbuminemia. Nevertheless, there were several limitations\u0026nbsp;associated with the\u0026nbsp;the present study. First, this study is a cross-sectional study, hence unable to completely understand the impact of dynamic changes in albumin on anorexia development in MHD patients. Second, this study only investigated 319 effective samples from three blood purification centers, and\u0026nbsp;the sample size should be increased\u0026nbsp;for further analysis in the future. Third, due to the lack of some data in the blood purification center, this study did not distinguish\u0026nbsp;between different\u0026nbsp;HDF patients,\u0026nbsp;and\u0026nbsp;so it\u0026nbsp;was\u0026nbsp;impossible to explore the effect of HDF on\u0026nbsp;the serum albumin levels. Finally, many studies have shown that hypoproteinemia and anorexia can also be closely associated with some laboratory indicators (e.g., NPY, IL6, cholecystokinin, ghrelin, leptin, etc.)\u003csup\u003e10,11,32,38-41\u003c/sup\u003e \u0026nbsp;but we were unable to explore these indicators further due to the current lack of availability of appropriate resources.\u003c/p\u003e\n\u003cp\u003eIn conclusion,\u0026nbsp;hypoalbuminemia and anorexia are common and\u0026nbsp;closely related\u0026nbsp;in MHD patients. With\u0026nbsp;an\u0026nbsp;increase of age, the incidence\u0026nbsp;of hypoalbuminemia and anorexia will increase, and the quality of life of MHD patients will decrease.\u0026nbsp;Therefore, preventing\u0026nbsp;low BMI and serum total calcium and increasing dialysis frequency\u0026nbsp;could\u0026nbsp;significantly reduce the incidence of hypoalbuminemia.\u0026nbsp;In the future, we aim to develop targeted intervention programs to reduce the incidence of both anorexia and hypoalbuminemia by modifying the relevant influencing factors to significantly improve the overall quality of life of MHD patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe practical applications\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study mainly investigated the relationship between hypoalbuminemia and anorexia in maintenance hemodialysis patients, and analyzed the influence of age on both and quality of life. It can provide new ideas and data support for the study of nutritional intervention in MHD patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study complied with the principles of the Declaration of Helsinki and was approved by the Ethics Committee of the First Affiliated Hospital of Guangxi Medical University., Nanning, Guangxi. We obtained written informed consent from all participants enrolled.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank all volunteers who participated in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZY designed the study. XTQ conducted study and wrote the manuscript. XTQ and BLZ\u003csup\u003e※\u003c/sup\u003e\u0026nbsp; collected the data. GPL and YLH\u003csup\u003e※\u003c/sup\u003e edited various versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data during the study appear in the submitted article; further inquiries are available from the corresponding author by request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eKovesdy CP, Kalantar-Zadeh K. Why is protein-energy wasting associated with mortality in chronic kidney disease? \u003cem\u003eSemin Nephrol\u003c/em\u003e. 2009;29(1):3-14\u003c/li\u003e\n\u003cli\u003eSabatino A, Piotti G, Cosola C et al. Dietary protein and nutritional supplements in conventional hemodialysis. \u003cem\u003eSemin Dial\u003c/em\u003e. 2018;31(6):583-591\u003c/li\u003e\n\u003cli\u003eFouque D, Kalantar-Zadeh K, Kopple J et al. 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Association Between Hemodiafiltration and Hypoalbuminemia in Middle-Age Hemodialysis Patients. \u003cem\u003eMedicine (Baltimore)\u003c/em\u003e. 2016;95(15):e3334\u003c/li\u003e\n\u003cli\u003eImrie CW, Allam BF, Ferguson JC. Hypocalcaemia of acute pancreatitis: the effect of hypoalbuminaemia. \u003cem\u003eCurr Med Res Opin\u003c/em\u003e. 1976;4(2):101-16\u003c/li\u003e\n\u003cli\u003eGuney I, Atalay H, Solak Y et al. Poor quality of life is associated with increased mortality in maintenance hemodialysis patients: a prospective cohort study. \u003cem\u003eSaudi J Kidney Dis Transpl\u003c/em\u003e. 2012;23(3):493-9\u003c/li\u003e\n\u003cli\u003eGrunfeld C, Zhao C, Fuller J et al. Endotoxin and cytokines induce expression of leptin, the ob gene product, in hamsters. \u003cem\u003eJ Clin Invest\u003c/em\u003e. 1996;97(9):2152-7\u003c/li\u003e\n\u003cli\u003eKalantar-Zadeh K, Block G, McAllister CJ, Humphreys MH, Kopple JD. Appetite and inflammation, nutrition, anemia, and clinical outcome in hemodialysis patients. \u003cem\u003eAm J Clin Nutr\u003c/em\u003e. 2004;80(2):299-307\u003c/li\u003e\n\u003cli\u003eNusken KD, Groschl M, Rauh M et al. Effect of renal failure and dialysis on circulating ghrelin concentration in children. \u003cem\u003eNephrol Dial Transplant\u003c/em\u003e. 2004;19(8):2156-7\u003c/li\u003e\n\u003cli\u003eMontazerifar F, Karajibani M, Gorgij F, Akbari O. Malnutrition Markers and Serum Ghrelin Levels in Hemodialysis Patients. \u003cem\u003eInt Sch Res Notices\u003c/em\u003e. 2014;2014:765895\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Comparison of general and clinical data between\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ehypoalbuminemia\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;group and no-\u003c/strong\u003e \u003cstrong\u003ehypoalbuminemia group\u003c/strong\u003e\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003e\u003cstrong\u003eItems\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall cohort\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=319\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo-\u003c/strong\u003e \u003cstrong\u003ehypoalbuminemia\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eN=248(77.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e\u003cstrong\u003ehypoalbuminemia \u0026nbsp;N=71(22.3%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026chi;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u003cem\u003e2/t\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eAge, years \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e54.80\u0026plusmn;15.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e53.36\u0026plusmn;15.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e59.82\u0026plusmn;14.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e-3.157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eMale, number (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e200(62.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e159(64.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e41(57.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e0.224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.636\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eDialysis age, months\u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e45.8\u0026plusmn;39.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e47.96\u0026plusmn;38.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e38.07\u0026plusmn;38.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e1.891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eWeekly\u0026nbsp;dialysis frequency,\u0026nbsp;number \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e2.70\u0026plusmn;0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e2.75\u0026plusmn;0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e2.49\u0026plusmn;0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e4.668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eBMI,\u0026nbsp;kg/㎡\u0026nbsp;\u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e22.25\u0026plusmn;3.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e22.54\u0026plusmn;3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e21.24\u0026plusmn;3.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e2.656\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eSerum scratinine, umoI/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e102.12\u0026plusmn;21.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e893.41\u0026plusmn;312.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e943.18\u0026plusmn;318.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e-1.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eiPTH,\u0026nbsp;pg/ml\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e495.47\u0026plusmn;404.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e488.78\u0026plusmn;398.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e518.84\u0026plusmn;425.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e-0.552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.581\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003ePi, mmol/L \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e1.81\u0026plusmn;0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e1.79\u0026plusmn;0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e1.88\u0026plusmn;0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e-1.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.288\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eK, mmol/L \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e4.73\u0026plusmn;0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e4.65\u0026plusmn;0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e4.88\u0026plusmn;0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e-1.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eTCa, mmol/L \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e2.21\u0026plusmn;0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e2.24\u0026plusmn;0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e2.11\u0026plusmn;0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e3.478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eAnorexia, number (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e109(34.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e66(26.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e43(60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e12.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eDiabetes, number (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e49(15.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e38(15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e11(15.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.976\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eSF12-Mental\u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e36.58\u0026plusmn;5.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e36.92\u0026plusmn;5.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e35.37\u0026plusmn;5.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e2.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eSF12-Physical\u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e34.69\u0026plusmn;6.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e35.50\u0026plusmn;6.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e31.85\u0026plusmn;5.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e4.338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eSymptom\u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e72.17\u0026plusmn;12.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e73.00\u0026plusmn;12.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e69.25\u0026plusmn;11.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e2.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eEffects\u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e51.63\u0026plusmn;11.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e52.88\u0026plusmn;11.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e47.28\u0026plusmn;13.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e3.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"26.507713884992988%\"\u003e\n \u003cp\u003eBurden\u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.513323983169705%\"\u003e\n \u003cp\u003e14.97\u0026plusmn;13.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"21.1781206171108%\"\u003e\n \u003cp\u003e16.15\u0026plusmn;13.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"17.251051893408135%\"\u003e\n \u003cp\u003e10.83\u0026plusmn;12.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.994389901823282%\"\u003e\n \u003cp\u003e2.919\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.55539971949509%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBMI, Body Mass Index; iPTH, intact parathyroid hormone; SF12-Mental, SF-12 Mental Health Composite; SF12-Physical, SF-12 Physical Health Composite; SD, standard deviation; TCa, Serum total calcium; K, Serum Potassium; Pi, Serum phosphorus\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Association between anorexia and hypoalbuminemia on multiple logistic regression models\u003c/strong\u003e\u003c/p\u003e\n\u003ctable\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eB\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eWald\u0026chi;2\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eOR\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e95%CI\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003eCrude Model 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eAnorexia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e1.443\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e26.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e4.235\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e2.436-7.362\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003eCrude Model 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e9.424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e1.010-1.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003eAdjusted Model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eAnorexia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e1.238\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.375\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e10.904\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e3.447\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e1.654-7.185\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e-0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e9.678\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e0.861\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e0.784-0.946\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e4.782\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e1.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e1.003-1.049\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eWeekly dialysis frequency\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e-1.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e11.499\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e0.158-0.611\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eTCa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e-1.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e6.265\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e0.240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e0.078-0.733\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eSF12-Mental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e-0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e2.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e0.951\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e0.888-1.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eSF12-Physical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e-0.039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e1.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e0.243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e0.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e0.902-1.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eSymptom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e5.259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e1.040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e1.006-1.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eEffects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e-0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e1.484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e0.223\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e0.979\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e0.945-1.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"18.807339449541285%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"16.666666666666668%\"\u003e\n \u003cp\u003eBurden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.6452599388379205%\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.021406727828746%\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.314984709480122%\"\u003e\n \u003cp\u003e0.577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.562691131498472%\"\u003e\n \u003cp\u003e1.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.960244648318042%\"\u003e\n \u003cp\u003e0.977-1.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCrude model 1(univariate), Crude model 2(univariate), Adjusted model 2(adjusted for anorexia; BMI; age; weekly dialysis frequency; TCa; SF12-Mental; SF12-Physical; Symptom; Effects; Burden).\u003cbr\u003e\u003cem\u003eB\u003c/em\u003e, coefficient value; \u003cem\u003eSE\u003c/em\u003e, standard error; \u003cem\u003eOR\u003c/em\u003e, odds ratio; \u003cem\u003eCI\u003c/em\u003e, confidence interval\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hypoalbuminemia, Anorexia, Maintenance hemodialysis, Quality of life","lastPublishedDoi":"10.21203/rs.3.rs-2288603/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2288603/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction:\u003c/strong\u003e Hypoalbuminemia is commonly observed in maintenance hemodialysis (MHD) patients and can serve as an important predictor of death in MHD patients. Anorexia is one of the important factors leading to hypoalbuminemia in MHD patients, so the purpose of this study was to examine the possible association between hypoalbuminemia and anorexia in MHD patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Patients from three blood purification centers in Nanning, Guangxi, China, who met the inclusion criteria were selected. Anorexia was assessed by appetite assessment questionnaire. The presence of hypoalbuminemia was determined based on the level of serum albumin. Thereafter, an association between hypoalbuminemia and anorexia was analyzed using multiple logistics regression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 319 participants, age 54.80±15.41 (62.7% male), were included in the study. In this study,the prevalence of hypoalbuminemia was 22.3% (71) and the prevalence of anorexia was 34.2% (109). According to multiple logistics regression analysis, hypoalbuminemia and anorexia were independently correlated in Crude Model 1(\u003cem\u003eOR\u003c/em\u003e:4.235 95%\u003cem\u003eCI\u003c/em\u003e: 2.436 to 7.362 \u003cem\u003eP\u003c/em\u003e＜0.001) and Adjust Model (\u003cem\u003eOR\u003c/em\u003e:3.447 95%\u003cem\u003eCI\u003c/em\u003e:1.654 to 7.185\u003cem\u003e P\u003c/em\u003e=0.001). In addition, age and symptom score were established as important risk factors for hypoalbuminemia(\u003cem\u003eP\u003c/em\u003e＜0.001); Body Mass Index (BMI), weekly dialysis frequency and serum total calcium (TCa) were identified as protective factors for hypoalbuminemia(\u003cem\u003eP\u003c/em\u003e＜0.001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions: \u003c/strong\u003eAnorexia is an independent risk factor for the occurrence of hypoalbuminemia. In MHD patients, the incidence of anorexia and hypoalbuminemia can increase significantly with increasing age, and can lead to a significant decline in the quality of life. In the future, further studies are needed to further verify the relevant mechanisms between them, to provide reference for clinical intervention in MHD patients.\u003c/p\u003e","manuscriptTitle":"Association between anorexia and hypoalbuminemia in the patients undergoing maintenance hemodialysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-12-19 19:39:32","doi":"10.21203/rs.3.rs-2288603/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0347b832-97c0-46b4-8ba5-d0af654a382e","owner":[],"postedDate":"December 19th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-01-10T06:29:39+00:00","versionOfRecord":[],"versionCreatedAt":"2022-12-19 19:39:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2288603","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2288603","identity":"rs-2288603","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}