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Orthostatic hypotension is associated with malnutrition diagnosed by GLIM in elderly hypertensive patients

Abstract

Background

Orthostatic Hypotension (OH) and malnutrition, are common health problems in elderly hypertensive patients. This study aimed to analyze the relationship between malnutrition and OH in elderly hypertensive patients.

Methods

This is a cross-sectional single-center study. All participants underwent a Comprehensive Geriatric Assessment (CGA), in which malnutrition was defined according to the Global Leadership Initiative on Malnutrition (GLIM) criteria based on four different methods of diagnosing muscle mass loss. Furthermore, the accuracy of these methods was verified by Receiver Operating Characteristic (ROC) analysis. Univariate and multivariate logistic regression analyses were used to identify risk factors for OH in elderly hypertensive patients.

Results

For GLIM criteria, when Fat-Free Mass Index (FFMI) was the gold standard for muscle mass loss, the Area Under ROC Curve (AUC) values for Upper Arm Circumference (UAC), Calf Circumference (CC), and Hand Grip Strength (HGS) were 0.784, 0.805, and 0.832, with moderate accuracy in diagnosing malnutrition. Multivariate analysis showed that females, Diabetes Mellitus (DM), diuretics, and malnutrition diagnosed by GLIM-UAC were risk factors for OH in elderly hypertensive patients.

Conclusion

Prompt detection of malnutrition in the elderly and attention to changes in UAC may be critical. Similarly, we should strengthen medication and disease management in elderly hypertensive patients.

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Introduction

According to the World Health Organization (WHO), the global population over the age of 60 will exceed 1.2 billion by 2025. The aging process in the elderly often leads to a degradation of the function of the blood pressure regulatory system, which results in a significant increase in the incidence of Orthostatic Hypotension (OH) [1, 2]. OH, is defined as a clinical manifestation of a 20 mmHg drop in systolic blood pressure or a 10 mmHg drop in diastolic blood pressure [3]. Available data suggest that the potential prevalence of OH in older adults over 65 years is generally 30%[4], and another study showed that about 84.4% of elderly hospitalized patients over the age of 75 suffered from OH [5]. The most common comorbidity of OH is Hypertension (HTN) [6]. The presence of OH can complicate the management of patients with HTN, as treating one may worsen the other [7]. In addition, older adults with HTN and OH had a more than a two-fold increased risk of falls [8]. Therefore, OH in elderly hypertensive patients should be more concerned.

Moreover, malnutrition is an important geriatric syndrome, which refers to insufficient, excessive, or abnormal nutrient intake, resulting in incompatibility with the body’s nutritional needs, adversely affecting the body’s morphological functions, and ultimately leading to adverse events such as sarcopenia and frailty [9,10,11,12,13]. In addition, the imbalance and gait variability caused by the decrease in muscle mass and muscle strength associated with sarcopenia can increase the probability of falls in the elderly [14]. Epidemiological studies have shown that the prevalence of malnutrition in hospitalized elderly is 30–61% [15]. So the diagnosis of malnutrition is crucial. To date, although there is no consensus on the assessment of malnutrition, various screening tools have been developed. The Global Leadership Initiative on Malnutrition (GLIM), the latest consensus, is a two-step diagnostic process. GLIM is widely used in many studies, and one of the points of contention is how to define muscle mass loss. Although dual-energy X-ray absorptiometry (DXA) and Bioelectrical Impedance Analysis (BIA) are recommended for measuring muscle mass, they have the disadvantage of being costly and time-consuming [16]. The newly proposed method of assessing lower extremity muscle thickness by ultrasound to diagnose muscle mass is equally complex [17]. Therefore, physical examination or anthropological measures, including Upper Arm Circumference (UAC), Calf Circumference (CC), and Hand Grip Strength (HGS) are often used for estimation, but their accuracy remains to be verified.

Malnutrition and malnutrition risk were risk factors for OH in a study using a Mini-Nutrition Assessment (MNA) as a diagnostic method [18]. And it is thought that this may be due to the nutritional-related loss of muscle mass and the effect of muscle tone on vascular and autonomic nerve function, leading to OH. However, this was only a study conducted in outpatient older adults, and we conducted this study to examine the relationship between OH and malnutrition in hospitalized older adults with HTN. In this article, we will focus on malnutrition and OH prevalence, verify the accuracy of the different methods measuring muscle mass loss, and analyze the influencing factors of OH in hypertensive elderly patients to provide a theoretical basis for subsequent precise prevention and interventions.

Methods

Design, setting and sample

Our observational study was conducted at the Zhejiang Hospital, Hangzhou, China, from 15 to 2015 to 18 February 2020. According to the Declaration of Helsinki, each subject provided written informed consent before conducting this study.

Variables and measurements

All patients completed the Comprehensive Geriatric Assessment (CGA), which involved an investigation of disease and medication history. Disease investigations included OH, HTN, Coronary Heart Disease (CHD), Chronic Obstructive Pulmonary Disease (COPD), and Diabetes Mellitus (DM). Drug investigations included Angiotensin-Converting Enzyme Inhibitor (ACEI), Angiotensin Receptor Blocker (ARB), Beta-Blocker (BB), Calcium Channel Blocker (CCB), Psychotropic, and statins. At the same time, questionnaires including Mini-Mental State Examination (MMSE), Instrumental Activities of Daily Living (IADL), and 15-item Geriatric Depression Scale (GDS-15) were completed.

The diagnosis of OH and HTN was conducted based on blood pressure measurements. We diagnosed OH with a transition from supine to standing, a 20 mmHg drop in systolic blood pressure, and a 10 mmHg drop in diastolic blood pressure within three minutes of the test [19]. And the diagnosis of HTN was defined according to relevant guidelines as systolic blood pressure ≥ 140 and/or diastolic blood pressure ≥ 90 mmHg, after repeating the measurement multiple times on different days [20].

Our study used the latest consensus, GLIM, to diagnose malnutrition. GLIM is based on MNA-SF [21] to complete a two-step process that includes a clinical phenotype, weight loss, low Body Mass Index(BMI) and low muscle mass loss; and an etiological phenotype, reduced food intake or absorption, inflammation, or disease burden.

Because of the complexity of indicators to monitor the inflammatory state, it was not considered in this study. And disease burden referred to most chronic organ diseases, including heart failure, COPD, chronic kidney or liver disease, and cancer [22]. Muscle mass loss took four different diagnostic forms. Subjects received a BIA measurement ( Inbody S10) to record Fat-Free Mass Index (FFMI) values and used a grip dynamometer to measure the dominant hand three times to select the maximum value. Based on resistance and reactance at 50 kHz, Fat-Free Mass (FFM) was calculated according to the Geneva equation. Subsequently, FFMI was calculated as FFM/height2 [23]. CC and UAC were measured with a tape measure while the participant was standing. Tape around the thickest part of the arm biceps to get UAC, and circle around the thickest part of the calf to get CC (Table 1).

Table 1 Cut off values for the phenotype and etiologic criteria of GLIM

Statistical analysis

Data analysis was completed using IBM SPSS software Version 26.0 for Windows. Quantitative variables were expressed as mean ± standard deviation. Quantitative variable distributions were assessed using the Kolmogorov-Smirnov test. Differences between quantitative variables were analyzed using Student’s t-test and nonparametric tests (Mann-Whitney) for variables that did not follow a normal distribution. Receiver operating characteristic (ROC) curves were estimated for each muscle mass loss diagnosed method of GLIM. The area under the curve of ROC (AUC) was used to estimate the discriminative ability. The indications for the diagnostic values were as follows: 0.5, none; 0.5 to 0.7, poor; 0.7 to 0.9, moderate; and 0.9 to 1, 2, good. We designed a multivariate logistic regression model. The dependent variable was OH. A multiple logistic regression model included factors identified as potentially significant (p < 0.05) in univariate analysis. A P-value of < 0.05 was considered statistically significant.

Results

In the datasets, we enrolled 532 patients, 157 patients were excluded because of incomplete clinical data (n = 132), active tumor (n = 10), and clinical diagnosis of acute heart, liver, and kidney injury (n = 15). The final study population consisted of 375 patients.

Characteristics of the subgroup based on OH

Table 2 shows the characteristics of the total study population. Of the participants, the median age was 86 years, and 55.20% were males. More than half participants were dentures (65.55%) and living alone (59.47%). Patients were divided into two groups according to the presence of OH. Malnutrition diagnosed by GLIM-UAC and GLIM-HGS, the proportion of males and the use of diuretics were statistically significantly different between the OH-positive and OH-negative groups.

Table 2 General characteristics

Nutritional screening and evaluation results

The incidence of malnutrition risk with MNA-SF ≤ 11 points was 42.67%. And the overall malnutrition rate was 45.07%. Patients who met each criterion met the malnutrition status are shown in Table 3. In addition, the GLIM defined in this study set different criteria for muscle mass loss, and AUC calculated by using FFMI-based diagnosis of malnutrition as the gold standard indicated that all three screening tools had a moderate effect (AUC of 0.784, 0.805, and 0.832 for UAC, CC, and HGS) (Fig. 1).

Table 3 The prevalence of patients meeting each criterion of the GLIM framework
Fig. 1
figure 1

Receiver operating characteristic (ROC) curve for prediction of malnutrition by glim, the diagnosis of muscle mass is based on the FFMI, CC, UAC, and HGS.

Analysis of the influencing factors of OH in hypertensive patients

After controlling for potential confounders, univariate and multivariate analyses to assess risk and protective factors for OH in elderly hypertensive patients. OH was associated with gender, DM, and GLIM-UAC in hypertensive patients. Male was its protective factor (Odds Ratio (OR) 0.433; 95% Confidence Interval (CI) 0.241–0.780; p = 0.005). DM, diuretics and GLIM-UAC were risk factors (OR, 1.895; 95%CI, 1.017–3.534; p = 0.044), (OR, 2.667; 95%CI, 1.517–4.688; p = 0.001), (OR, 2.375; 95%CI, 1.066–5.293; p = 0.034) (Table 4).

Table 4 Univariate and multivariate analyses assess risk factors for patients with OH

Discussion

To our knowledge, the results of our research showed that the prevalence of malnutrition and OH were 45.07% and 18.13%. CC, UAC, and HGS all three screening tools had a moderate effect in diagnosing malnutrition. It also revealed that malnutrition diagnosed by GLIM-UAC, DM, female and long-term use of diuretics were risk factors for OH in hypertensive elderly patients.

Our study used the latest consensus, GLIM, to diagnose malnutrition. This is an easy way for clinicians to apply the available tools and methods [22]. In our sample, the results of the three muscle mass loss diagnosing tools, HGS, CC, and UAC, were validated to have a moderate accuracy in diagnosing malnutrition, using FFMI as the gold standard. Sanchez-Rodriguez D used the same methodology as ours to reach similar conclusions. But they were in the community, and we were in the elderly who were hospitalized [17]. Similarly, a survey in Spain yielded similar results [24]. Therefore, we believe that measurements of CC, UAC, and HGS can be used in place of FFMI in limited settings such as primary hospitals or communities, and recommended to first refine the measurement of CC, HGS, and UAC in high-risk populations.

Previous studies have reported that both malnutrition and malnutrition risk were associated with OH [18, 25]. Our findings suggested that malnutrition diagnosed by GLIM-UAC is a risk factor for OH in elderly hypertensive patients. However, this was not observed in several other diagnoses such as GLIM-CC, which may be the reason for the presence of invisible lower extremity edema in the elderly, affecting the results of CC and BIA measurements. Vitamins as one the important nutrients, numerous studies have found that vitamin D plays an important role in OH [26], and this conclusion has been verified in both men and women [27, 28]. It is considered that vitamin D has a role in blood pressure control and intravascular volume, vitamin D deficiency may promote OH through this mechanism. Vitamin D affects the vasopressor response by down regulating the renin-angiotensin-aldosterone system and may be involved in regulating the vascular response in the upright state. At the same time, vitamin D metabolites modulate the gene expression of neurotrophic factors, resulting in decreased compensatory mechanisms during standing [29]. However, studies conducted in older Irish communities contradicted our conclusions [26, 30]. Because malnutrition is preventable, nutritional status should be examined when assessing changes in blood pressure, especially in elderly hypertensive patients. Meanwhile, as another important nutrient, about 50%-75% of protein is stored in skeletal muscle [31]. Protein intake is a master regulator of muscle protein metabolism, affecting the regulation of the dynamic and transient balance between muscle protein synthesis (MPS) and muscle protein breakdown (MPB). Inadequate protein intake can lead to sarcopenia and frailty through multiple mechanisms [32]. And in present, the correlation between OH and muscle mass reduction has been confirmed by multiple studies [33,34,35].

Our findings proposed that long-term diuretic use and DM were risk factors for OH. Diuretics increase natriuresis and lead to a decrease in urine output, especially in the elderly. Loop diuretics also increase venous volume, which reduces venous return and cardiac output. Several studies reported a significant association of diuretics with OH [36, 37]. Therefore, drug screening is recommended as a first-line approach to OH’s diagnostic and therapeutic workup. It should be aimed at evaluating their indications and benefits to assess discontinuation or dose reduction. With DM being a common condition, DM-related autonomic dysfunction is often considered to be the main mechanism leading to delayed blood pressure recovery as it impairs the pressure reflex-mediated response to blood pressure recovery from hypotension. Similarly, it has been shown that DM patients are significantly more likely to experience OH after thirty seconds of standing than those without DM [38].

This study has certain clinical significance. Considering the risk factors derived from the results, medication and disease management should be included in the actual health management of older adults, especially those with HTN, DM and chronic diuretic use. In addition, nutritional screening should be strengthened, and early detection and diagnosis of malnutrition may facilitate the detection of OH. However, there were some limitations in the present study. First, our study is a cross-sectional, single-center study, and observed associations could not establish a causal nexus between malnutrition and OH. And next, the specific types of diuretics and the intake amount of nutrients such as vitamins and proteins were not analyzed and compared. Further prospective studies are needed to explore the relationship between OH and malnutrition in elderly hypertensive hospitalized patients.

Conclusion

This study demonstrated that CC, UAC, and HGS have moderate to moderate accuracy in diagnosing malnutrition in elderly hypertensive populations. We also found malnutrition diagnosed by GLIM-UAC, females, DM, and long-term diuretic use were risk factors for OH in elderly hypertensive patients. Therefore, management of disease, medication and nutritional status is necessary.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Code Availability

Not applicable.

Abbreviations

FFMI:

fat-free mass index

UAC:

upper arm circumference

CC:

calf circumference

HGS:

hand grip strength

BMI:

body mass index

OH:

orthostatic hypotension

CHD:

coronary heart disease

COPD:

chronic obstructive pulmonary disease

DM:

diabetes mellitus

MMSE:

mini-mental state examination

IADL:

instrumental activity of daily living

ADL:

activity of daily living

GDS-15:

15-item geriatric depression scale

ICI:

international consultation on incontinence question

CGA:

comprehensive geriatric assessment

ACEI:

angiotensin-converting enzyme inhibitor

ARB:

angiotensin receptor blocker

BB:

beta-blocker

CCB:

calcium channel blocker

PSQI:

pittsburgh sleep quality index

HTN:

hypertension

GLIM:

global leadership initiative on malnutrition

DXA:

dual-energy x-ray absorptiometry

BIA:

bioelectrical impedance analysis

MNA:

mini-nutrition assessment

MNA-SF:

short-form mini-nutrition assessment

OR:

Odds ratio

References

  1. Kearney F, Moore A. Treatment of combined hypertension and orthostatic hypotension in older adults: more questions than answers still remain. Expert Rev Cardiovasc Ther. 2009;7(6):557–60.

    Article  PubMed  Google Scholar 

  2. Drevet S, Gavazzi G. Dénutrition du sujet âgé [Undernutrition of the elderly]. Rev Med Interne. 2019;40(10):664–9.

    Article  CAS  PubMed  Google Scholar 

  3. Franklin SS, Larson MG, Khan SA, et al. Does the relation of blood pressure to coronary heart disease risk change with aging? The Framingham Heart Study. Circulation. 2001;103(9):1245–9.

    Article  CAS  PubMed  Google Scholar 

  4. Maule S, Papotti G, Naso D, Magnino C, Testa E, Veglio F. Orthostatic hypotension: evaluation and treatment. Cardiovasc Hematol Disord Drug Targets. 2007;7(1):63–70.

    Article  CAS  PubMed  Google Scholar 

  5. Wojszel ZB, Kasiukiewicz A, Magnuszewski L. Health and Functional Determinants of Orthostatic Hypotension in Geriatric Ward Patients: A Retrospective Cross Sectional Cohort Study. J Nutr Health Aging. 2019;23(6):509–17.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Wahba A, Shibao CA, Muldowney JAS, Peltier A, Habermann R, Biaggioni I. Management of Orthostatic Hypotension in the Hospitalized Patient: A Narrative Review. Am J Med. 2022;135(1):24–31.

    Article  CAS  PubMed  Google Scholar 

  7. Biaggioni I. Orthostatic Hypotension in the Hypertensive Patient. Am J Hypertens. 2018;31(12):1255–9.

    Article  CAS  PubMed  Google Scholar 

  8. Gangavati A, Hajjar I, Quach L, et al. Hypertension, orthostatic hypotension, and the risk of falls in a community-dwelling elderly population: the maintenance of balance, independent living, intellect, and zest in the elderly of Boston study [published correction appears in J Am Geriatr Soc. 2011 May;59(5):960]. J Am Geriatr Soc. 2011;59(3):383–389.

  9. Wei K, Nyunt MS, Gao Q, Wee SL, Yap KB, Ng TP. Association of Frailty and Malnutrition With Long-term Functional and Mortality Outcomes Among Community-Dwelling Older Adults: Results From the Singapore Longitudinal Aging Study 1. JAMA Netw Open. 2018;1(3):e180650.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Agostini F, Bernetti A, Di Giacomo G, Viva MG, Paoloni M, Mangone M, et al. Rehabilitative Good Practices in the Treatment of Sarcopenia: A Narrative Review. Am J Phys Med Rehabil. 2021;100(3):280–7.

    Article  PubMed  Google Scholar 

  11. de Sire A, Ferrillo M, Lippi L, Agostini F, de Sire R, Ferrara PE, et al. Sarcopenic Dysphagia, Malnutrition, and Oral Frailty in Elderly: A Comprehensive Review. Nutrients. 2022;14(5):982.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Agarwal E, Miller M, Yaxley A, Isenring E. Malnutrition in the elderly: a narrative review. Maturitas. 2013;76(4):296–302.

    Article  CAS  PubMed  Google Scholar 

  13. Field LB, Hand RK. Differentiating malnutrition screening and assessment: a nutrition care process perspective. J Acad Nutr Diet. 2015;115(5):824–8.

    Article  PubMed  Google Scholar 

  14. Rodrigues F, Domingos C, Monteiro D, Morouço P. A Review on Aging, Sarcopenia, Falls, and Resistance Training in Community-Dwelling Older Adults. Int J Environ Res Public Health. 2022;19(2):874.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Ruiz AJ, Buitrago G, Rodríguez N, et al. Clinical and economic outcomes associated with malnutrition in hospitalized patients. Clin Nutr. 2019;38(3):1310–6.

    Article  PubMed  Google Scholar 

  16. Sanchez-Rodriguez D, Locquet M, Bruyère O, et al. Prediction of 5-year mortality risk by malnutrition according to the GLIM format using seven pragmatic approaches to define the criterion of loss of muscle mass. Clin Nutr. 2021;40(4):2188–99.

    Article  PubMed  Google Scholar 

  17. Leigheb M, de Sire A, Colangelo M, Zagaria D, Grassi FA, Rena O, et al. Sarcopenia Diagnosis: Reliability of the Ultrasound Assessment of the Tibialis Anterior Muscle as an Alternative Evaluation Tool. Diagnostics (Basel). 2021;11(11):2158.

    Article  Google Scholar 

  18. Kocyigit SE, Ates Bulut E, Assoc. Professor, Aydin AE, Isik AT, Professor. Improvement of nutritional status enhances cognitive and physical functions in older adults with orthostatic hypotension. Nutrition. 2021;90:111261.

    Article  CAS  PubMed  Google Scholar 

  19. Consensus statement on the. definition of orthostatic hypotension, pure autonomic failure, and multiple system atrophy. The Consensus Committee of the American Autonomic Society and the American Academy of Neurology. Neurology. 1996;46(5):1470.

    Article  Google Scholar 

  20. Unger T, Borghi C, Charchar F, et al. 2020 International Society of Hypertension Global Hypertension Practice Guidelines. Hypertension. 2020;75(6):1334–57.

    Article  CAS  PubMed  Google Scholar 

  21. Rubenstein LZ, Harker JO, Salvà A, Guigoz Y, Vellas B. Screening for undernutrition in geriatric practice: developing the short-form mini-nutritional assessment (MNA-SF). J Gerontol A Biol Sci Med Sci. 2001;56(6):M366–72.

    Article  CAS  PubMed  Google Scholar 

  22. Cederholm T, Jensen GL, Correia MITD, et al. GLIM criteria for the diagnosis of malnutrition - A consensus report from the global clinical nutrition community. Clin Nutr. 2019;38(1):1–9.

    Article  CAS  PubMed  Google Scholar 

  23. Kyle UG, Genton L, Karsegard L, Slosman DO, Pichard C. Single prediction equation for bioelectrical impedance analysis in adults aged 20–94 years. Nutrition. 2001;17(3):248–53.

    Article  CAS  PubMed  Google Scholar 

  24. Contreras-Bolívar V, Sánchez-Torralvo FJ, Ruiz-Vico M, et al. GLIM Criteria Using Hand Grip Strength Adequately Predict Six-Month Mortality in Cancer Inpatients. Nutrients. 2019;11(9):2043.

    Article  PubMed Central  Google Scholar 

  25. Kocyigit SE, Soysal P, Ates Bulut E, Isik AT. Malnutrition and Malnutrition Risk Can Be Associated with Systolic Orthostatic Hypotension in Older Adults. J Nutr Health Aging. 2018;22(8):928–33.

    Article  CAS  PubMed  Google Scholar 

  26. Laird EJ, McNicholas T, O’Halloran AM, et al. Vitamin D Status Is Not Associated With Orthostatic Hypotension in Older Adults. Hypertension. 2019;74(3):639–44.

    Article  CAS  PubMed  Google Scholar 

  27. McCarroll KG, Robinson DJ, Coughlan A, Healy M, Kenny RA, Cunningham C. Vitamin D and orthostatic hypotension. Age Ageing. 2012;41(6):810–3.

    Article  PubMed  Google Scholar 

  28. Annweiler C, Schott AM, Rolland Y, Beauchet O. Vitamin D deficiency is associated with orthostatic hypotension in oldest-old women. J Intern Med. 2014;276(3):285–95.

    Article  CAS  PubMed  Google Scholar 

  29. Kalueff AV, Tuohimaa P. Neurosteroid hormone vitamin D and its utility in clinical nutrition. Curr Opin Clin Nutr Metab Care. 2007;10(1):12–9.

    Article  CAS  PubMed  Google Scholar 

  30. Gilani A, Ramsay SE, Welsh P, et al. Vitamin D deficiency is associated with orthostatic hypotension in older men: a cross-sectional analysis from the British Regional Heart Study. Age Ageing. 2021;50(1):198–204.

    Article  PubMed  Google Scholar 

  31. Fougère B, Vellas B, van Kan GA, Cesari M. Identification of biological markers for better characterization of older subjects with physical frailty and sarcopenia [retracted in: Transl Neurosci. 2020 Sep 11;11(1):334]. Transl Neurosci. 2015;6(1):103–110.

  32. Coelho-Junior HJ, Marzetti E, Picca A, Cesari M, Uchida MC, Calvani R. Protein Intake and Frailty: A Matter of Quantity, Quality, and Timing. Nutrients. 2020;12(10):2915.

    Article  PubMed Central  Google Scholar 

  33. Benton MJ, Silva-Smith AL, Spicher JM. Muscle Loss is Associated with Risk of Orthostatic Hypotension in Older Men and Women. J Frailty Aging. 2021;10(3):219–25.

    CAS  PubMed  Google Scholar 

  34. Soysal P, Kocyigit SE, Dokuzlar O, Ates Bulut E, Smith L, Isik AT. Relationship between sarcopenia and orthostatic hypotension. Age Ageing. 2020;49(6):959–65.

    Article  PubMed  Google Scholar 

  35. Kocyigit SE, Soysal P, Bulut EA, Aydin AE, Dokuzlar O, Isik AT. What is the relationship between frailty and orthostatic hypotension in older adults? J Geriatr Cardiol. 2019;16(3):272–9.

    PubMed  PubMed Central  Google Scholar 

  36. Sica DA, Carter B, Cushman W, Hamm L. Thiazide and loop diuretics. J Clin Hypertens (Greenwich). 2011;13(9):639–43.

    Article  CAS  Google Scholar 

  37. Kamaruzzaman S, Watt H, Carson C, Ebrahim S. The association between orthostatic hypotension and medication use in the British Women’s Heart and Health Study. Age Ageing. 2010;39(1):51–6.

    Article  PubMed  Google Scholar 

  38. Gannon J, Claffey P, Laird E, Newman L, Kenny RA, Briggs R. The cross-sectional association between diabetes and orthostatic hypotension in community-dwelling older people. Diabet Med. 2020;37(8):1299–307.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We sincerely thank the staff from the Geriatric Department of Zhejiang Hospital for their positive involvement in this study.

Funding

This study was supported by the National Key R&D Program Fund (Grant numbers 2020YFC2008606) and National Health and Family Planning Commission Scientific Research Fund (WKJ2012-2-001).

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Authors and Affiliations

Authors

Contributions

Conceptualization, Q.-Z.Z.,X.-J.C and S.-S.S.; formal analysis, Q.-Z.Z; writing—original draft preparation, Q.-Z.Z. and S.-S.S; investigation, J.-M.Z. and H.-L.G.; funding, X.-J.C.; All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Xujiao Chen.

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Ethical approval

The Ethics Committee of Zhejiang Hospital approved this study (2013–25), and each participant signed written informed consent. Our research complied with the guidelines for human studies and was conducted ethically in accordance with the World Medical Association Declaration of Helsinki.All participants gave written informed consent.

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Zhang, Q., Shen, S., Guan, H. et al. Orthostatic hypotension is associated with malnutrition diagnosed by GLIM in elderly hypertensive patients. BMC Geriatr 22, 866 (2022). https://doi.org/10.1186/s12877-022-03546-x

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Keywords

  • Orthostatic hypotension
  • Malnutrition
  • Muscle mass loss
  • CGA
  • Risk factors