Association of Dietary Antioxidant Potential with Sarcopenia in Hypertension

Xumin Xin

doi:10.31083/RCM27138

Information
Figures
References
Contents

Academic Editor

Peter Kokkinos

Download

[1]Jimenez-Gutierrez GE, Martínez-Gómez LE, Martínez-Armenta C, Pineda C, Martínez-Nava GA, Lopez-Reyes A. Molecular Mechanisms of Inflammation in Sarcopenia: Diagnosis and Therapeutic Update. Cells. 2022; 11: 2359. https://doi.org/10.3390/cells11152359.
- Google Scholar
[2]Tarantino G, Sinatti G, Citro V, Santini SJ, Balsano C. Sarcopenia, a condition shared by various diseases: can we alleviate or delay the progression? Internal and Emergency Medicine. 2023; 18: 1887–1895. https://doi.org/10.1007/s11739-023-03339-z.
- Google Scholar
[3]Xing E, Wan C. Prevalence of and factors associated with sarcopenia among elderly individuals with hypertension. The Journal of International Medical Research. 2022; 50: 3000605221110490. https://doi.org/10.1177/03000605221110490.
- Google Scholar
[4]Ata AM, Kara M, Ekiz T, Kara Ö, Culha MA, Ricci V, et al. Reassessing Sarcopenia in Hypertension: STAR and ACE Inhibitors Excel. International Journal of Clinical Practice. 2021; 75: e13800. https://doi.org/10.1111/ijcp.13800.
- Google Scholar
[5]Li M, Ji R, Liu X, Wu Y. Associations of metabolic syndrome and its components with sarcopenia, and the mediating role of insulin resistance: Findings from NHANES database. BMC Endocrine Disorders. 2024; 24: 203. https://doi.org/10.1186/s12902-024-01736-9.
- Google Scholar
[6]Can B, Kara O, Kizilarslanoglu MC, Arik G, Aycicek GS, Sumer F, et al. Serum markers of inflammation and oxidative stress in sarcopenia. Aging Clinical and Experimental Research. 2017; 29: 745–752. https://doi.org/10.1007/s40520-016-0626-2.
- Google Scholar
[7]Sinha-Hikim I, Sinha-Hikim AP, Parveen M, Shen R, Goswami R, Tran P, et al. Long-term supplementation with a cystine-based antioxidant delays loss of muscle mass in aging. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences. 2013; 68: 749–759. https://doi.org/10.1093/gerona/gls334.
- Google Scholar
[8]Diao H, Yan F, He Q, Li M, Zheng Q, Zhu Q, et al. Association between Dietary Inflammatory Index and Sarcopenia: A Meta-Analysis. Nutrients. 2023; 15: 219. https://doi.org/10.3390/nu15010219.
- Google Scholar
[9]Chen Y, Tang W, Li H, Lv J, Chang L, Chen S. Composite dietary antioxidant index negatively correlates with osteoporosis among middle-aged and older US populations. American Journal of Translational Research. 2023; 15: 1300–1308.
- Google Scholar
[10]Welch AA, Jennings A, Kelaiditi E, Skinner J, Steves CJ. Cross-Sectional Associations Between Dietary Antioxidant Vitamins C, E and Carotenoid Intakes and Sarcopenic Indices in Women Aged 18-79 Years. Calcified Tissue International. 2020; 106: 331–342. https://doi.org/10.1007/s00223-019-00641-x.
- Google Scholar
[11]Bo Y, Liu C, Ji Z, Yang R, An Q, Zhang X, et al. A high whey protein, vitamin D and E supplement preserves muscle mass, strength, and quality of life in sarcopenic older adults: A double-blind randomized controlled trial. Clinical Nutrition (Edinburgh, Scotland). 2019; 38: 159–164. https://doi.org/10.1016/j.clnu.2017.12.020.
- Google Scholar
[12]Liu Y, Liu X, Duan L, Zhao Y, He Y, Li W, et al. Associations of micronutrient dietary patterns with sarcopenia among US adults: a population-based study. Frontiers in Nutrition. 2024; 11: 1301831. https://doi.org/10.3389/fnut.2024.1301831.
- Google Scholar
[13]van Dronkelaar C, van Velzen A, Abdelrazek M, van der Steen A, Weijs PJM, Tieland M. Minerals and Sarcopenia; The Role of Calcium, Iron, Magnesium, Phosphorus, Potassium, Selenium, Sodium, and Zinc on Muscle Mass, Muscle Strength, and Physical Performance in Older Adults: A Systematic Review. Journal of the American Medical Directors Association. 2018; 19: 6–11.e3. https://doi.org/10.1016/j.jamda.2017.05.026.
- Google Scholar
[14]van Dijk M, Dijk FJ, Hartog A, van Norren K, Verlaan S, van Helvoort A, et al. Reduced dietary intake of micronutrients with antioxidant properties negatively impacts muscle health in aged mice. Journal of Cachexia, Sarcopenia and Muscle. 2018; 9: 146–159. https://doi.org/10.1002/jcsm.12237.
- Google Scholar
[15]Wang L, Yi Z. Association of the Composite dietary antioxidant index with all-cause and cardiovascular mortality: A prospective cohort study. Frontiers in Cardiovascular Medicine. 2022; 9: 993930. https://doi.org/10.3389/fcvm.2022.993930.
- Google Scholar
[16]Miao H, Liu Y, Tsai TC, Schwartz J, Ji JS. Association Between Blood Lead Level and Uncontrolled Hypertension in the US Population (NHANES 1999-2016). Journal of the American Heart Association. 2020; 9: e015533. https://doi.org/10.1161/JAHA.119.015533.
- Google Scholar
[17]Whelton PK, Carey RM, Aronow WS, Casey DE, Jr, Collins KJ, Dennison Himmelfarb C, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension. 2018; 71: e13–e115. https://doi.org/10.1161/HYP.0000000000000065.
- Google Scholar
[18]Chen W, Shi S, Jiang Y, Chen K, Liao Y, Huang R, et al. Association of sarcopenia with ideal cardiovascular health metrics among US adults: a cross-sectional study of NHANES data from 2011 to 2018. BMJ Open. 2022; 12: e061789. https://doi.org/10.1136/bmjopen-2022-061789.
- Google Scholar
[19]Maugeri A, Hruskova J, Jakubik J, Kunzova S, Sochor O, Barchitta M, et al. Dietary antioxidant intake decreases carotid intima media thickness in women but not in men: A cross-sectional assessment in the Kardiovize study. Free Radical Biology & Medicine. 2019; 131: 274–281. https://doi.org/10.1016/j.freeradbiomed.2018.12.018.
- Google Scholar
[20]Dai S, Shu D, Meng F, Chen Y, Wang J, Liu X, et al. Higher Risk of Sarcopenia in Older Adults with Type 2 Diabetes: NHANES 1999-2018. Obesity Facts. 2023; 16: 237–248. https://doi.org/10.1159/000530241.
- Google Scholar
[21]Yu B, Sun Y, Du X, Zhang H, Chen C, Tan X, et al. Age-specific and sex-specific associations of visceral adipose tissue mass and fat-to-muscle mass ratio with risk of mortality. Journal of Cachexia, Sarcopenia and Muscle. 2023; 14: 406–417. https://doi.org/10.1002/jcsm.13142.
- Google Scholar
[22]Rom O, Kaisari S, Aizenbud D, Reznick AZ. Sarcopenia and smoking: a possible cellular model of cigarette smoke effects on muscle protein breakdown. Annals of the New York Academy of Sciences. 2012; 1259: 47–53. https://doi.org/10.1111/j.1749-6632.2012.06532.x.
- Google Scholar
[23]Bu YL, Wang C, Zhao C, Lu X, Gao W. The association of alcohol consumption with the risk of sarcopenia: a dose-response meta-analysis. The American Journal of Drug and Alcohol Abuse. 2024; 50: 305–320. https://doi.org/10.1080/00952990.2023.2300049.
- Google Scholar
[24]Izzo A, Massimino E, Riccardi G, Della Pepa G. A Narrative Review on Sarcopenia in Type 2 Diabetes Mellitus: Prevalence and Associated Factors. Nutrients. 2021; 13: 183. https://doi.org/10.3390/nu13010183.
- Google Scholar
[25]Zhou S, Wu L, Si H, Shen B. Longitudinal Association between Uric Acid and Incident Sarcopenia. Nutrients. 2023; 15: 3097. https://doi.org/10.3390/nu15143097.
- Google Scholar
[26]Gao H, Wang J, Zou X, Zhang K, Zhou J, Chen M. High blood urea nitrogen to creatinine ratio is associated with increased risk of sarcopenia in patients with chronic obstructive pulmonary disease. Experimental Gerontology. 2022; 169: 111960. https://doi.org/10.1016/j.exger.2022.111960.
- Google Scholar
[27]Lee HS, Koh IH, Kim HS, Kwon YJ. Platelet and white blood cell count are independently associated with sarcopenia: A nationwide population-based study. Thrombosis Research. 2019; 183: 36–44. https://doi.org/10.1016/j.thromres.2019.09.007.
- Google Scholar
[28]Lin MH, Chiu SY, Chang PH, Lai YL, Chen PC, Ho WC. Hyperlipidemia and Statins Use for the Risk of New Diagnosed Sarcopenia in Patients with Chronic Kidney: A Population-Based Study. International Journal of Environmental Research and Public Health. 2020; 17: 1494. https://doi.org/10.3390/ijerph17051494.
- Google Scholar
[29]Kim H, Yoo S, Park YS, Park SG. Low dietary energy intake is associated with sarcopenia in cancer survivors: An analysis based on the Korean National Health and Nutrition Examination Survey 2008-2011. Nutrition Research. 2018; 53: 15–22. https://doi.org/10.1016/j.nutres.2018.01.004.
- Google Scholar
[30]Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL, Jr, et al. Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension. 2003; 42: 1206–1252. https://doi.org/10.1161/01.HYP.0000107251.49515.c2.
- Google Scholar
[31]Lewis LN, Hayhoe RPG, Mulligan AA, Luben RN, Khaw KT, Welch AA. Lower Dietary and Circulating Vitamin C in Middle- and Older-Aged Men and Women Are Associated with Lower Estimated Skeletal Muscle Mass. The Journal of Nutrition. 2020; 150: 2789–2798. https://doi.org/10.1093/jn/nxaa221.
- Google Scholar
[32]Abete I, Konieczna J, Zulet MA, Galmés-Panades AM, Ibero-Baraibar I, Babio N, et al. Association of lifestyle factors and inflammation with sarcopenic obesity: data from the PREDIMED-Plus trial. Journal of Cachexia, Sarcopenia and Muscle. 2019; 10: 974–984. https://doi.org/10.1002/jcsm.12442.
- Google Scholar
[33]Mulligan AA, Hayhoe RPG, Luben RN, Welch AA. Positive Associations of Dietary Intake and Plasma Concentrations of Vitamin E with Skeletal Muscle Mass, Heel Bone Ultrasound Attenuation and Fracture Risk in the EPIC-Norfolk Cohort. Antioxidants. 2021; 10: 159. https://doi.org/10.3390/antiox10020159.
- Google Scholar
[34]Otsuka Y, Iidaka T, Horii C, Muraki S, Oka H, Nakamura K, et al. Dietary Intake of Vitamin E and Fats Associated with Sarcopenia in Community-Dwelling Older Japanese People: A Cross-Sectional Study from the Fifth Survey of the ROAD Study. Nutrients. 2021; 13: 1730. https://doi.org/10.3390/nu13051730.
- Google Scholar
[35]Sahni S, Dufour AB, Fielding RA, Newman AB, Kiel DP, Hannan MT, et al. Total carotenoid intake is associated with reduced loss of grip strength and gait speed over time in adults: The Framingham Offspring Study. The American Journal of Clinical Nutrition. 2021; 113: 437–445. https://doi.org/10.1093/ajcn/nqaa288.
- Google Scholar
[36]van Dijk M, Dijk FJ, Bunschoten A, van Dartel DAM, van Norren K, Walrand S, et al. Improved muscle function and quality after diet intervention with leucine-enriched whey and antioxidants in antioxidant deficient aged mice. Oncotarget. 2016; 7: 17338–17355. https://doi.org/10.18632/oncotarget.7800.
- Google Scholar
[37]Kara M, Kara Ö, Ceran Y, Kaymak B, Kaya TC, Çıtır BN, et al. SARcopenia Assessment in Hypertension: The SARAH Study. American Journal of Physical Medicine & Rehabilitation. 2023; 102: 130–136. https://doi.org/10.1097/PHM.0000000000002045.
- Google Scholar
[38]Griendling KK, Camargo LL, Rios FJ, Alves-Lopes R, Montezano AC, Touyz RM. Oxidative Stress and Hypertension. Circulation Research. 2021; 128: 993–1020. https://doi.org/10.1161/CIRCRESAHA.121.318063.
- Google Scholar
[39]Liu S, Zhang L, Li S. Advances in nutritional supplementation for sarcopenia management. Frontiers in Nutrition. 2023; 10: 1189522. https://doi.org/10.3389/fnut.2023.1189522.
- Google Scholar
[40]Zhao L, Sun Y, Cao R, Wu X, Huang T, Peng W. Non-linear association between composite dietary antioxidant index and depression. Frontiers in Public Health. 2022; 10: 988727. https://doi.org/10.3389/fpubh.2022.988727.
- Google Scholar
[41]Cuthbertson D, Smith K, Babraj J, Leese G, Waddell T, Atherton P, et al. Anabolic signaling deficits underlie amino acid resistance of wasting, aging muscle. FASEB Journal: Official Publication of the Federation of American Societies for Experimental Biology. 2005; 19: 422–424. https://doi.org/10.1096/fj.04-2640fje.
- Google Scholar
[42]Baharirad N, Pasdar Y, Nachvak M, Ghavamzadeh S, Soroush A, Saber A, et al. The relationship of dietary total antioxidant capacity with sarcopenia and cardiometabolic biomarkers in type 2 diabetes patients. Physiological Reports. 2022; 10: e15190. https://doi.org/10.14814/phy2.15190.
- Google Scholar
[43]Papaioannou KG, Nilsson A, Nilsson LM, Kadi F. Healthy Eating Is Associated with Sarcopenia Risk in Physically Active Older Adults. Nutrients. 2021; 13: 2813. https://doi.org/10.3390/nu13082813.
- Google Scholar
[44]Kim J, Lee Y, Kye S, Chung YS, Kim KM. Association of vegetables and fruits consumption with sarcopenia in older adults: the Fourth Korea National Health and Nutrition Examination Survey. Age and Ageing. 2015; 44: 96–102. https://doi.org/10.1093/ageing/afu028.
- Google Scholar
[45]Barragán R, Sánchez-González C, Aranda P, Sorlí JV, Asensio EM, Portolés O, et al. Single and Combined Associations of Plasma and Urine Essential Trace Elements (Zn, Cu, Se, and Mn) with Cardiovascular Risk Factors in a Mediterranean Population. Antioxidants. 2022; 11: 1991. https://doi.org/10.3390/antiox11101991.
- Google Scholar
[46]Wang S, Nong X, Yang G. Selenium-Rich Diet Induces Myocardial Structural and Functional Abnormalities by Activating Caspase-9 and Caspase-3 in Gpx-1P198L-Overexpression Transgenic Mice. Medical Science Monitor. 2019; 25: 61–70. https://doi.org/10.12659/MSM.911120.
- Google Scholar
[47]Luu HN, Wen W, Li H, Dai Q, Yang G, Cai Q, et al. Are dietary antioxidant intake indices correlated to oxidative stress and inflammatory marker levels? Antioxidants & Redox Signaling. 2015; 22: 951–959. https://doi.org/10.1089/ars.2014.6212.
- Google Scholar
[48]Galarregui C, Zulet MÁ, Cantero I, Marín-Alejandre BA, Monreal JI, Elorz M, et al. Interplay of Glycemic Index, Glycemic Load, and Dietary Antioxidant Capacity with Insulin Resistance in Subjects with a Cardiometabolic Risk Profile. International Journal of Molecular Sciences. 2018; 19: 3662. https://doi.org/10.3390/ijms19113662.
- Google Scholar
[49]Kanno SI, Tomizawa A, Yomogida S, Hara A. Glutathione peroxidase 3 is a protective factor against acetaminophen induced hepatotoxicity in vivo and in vitro. International Journal of Molecular Medicine. 2017; 40: 748–754. https://doi.org/10.3892/ijmm.2017.3049.
- Google Scholar
[50]Viña J, Borrás C, Gambini J, Sastre J, Pallardó FV. Why females live longer than males? Importance of the upregulation of longevity-associated genes by oestrogenic compounds. FEBS Letters. 2005; 579: 2541–2545. https://doi.org/10.1016/j.febslet.2005.03.090.
- Google Scholar
[51]Barp J, Araújo ASR, Fernandes TRG, Rigatto KV, Llesuy S, Belló-Klein A, et al. Myocardial antioxidant and oxidative stress changes due to sex hormones. Brazilian Journal of Medical and Biological Research. 2002; 35: 1075–1081. https://doi.org/10.1590/s0100-879x2002000900008.
- Google Scholar
[52]Veeramani S, Chou YW, Lin FC, Muniyan S, Lin FF, Kumar S, et al. Reactive oxygen species induced by p66Shc longevity protein mediate nongenomic androgen action via tyrosine phosphorylation signaling to enhance tumorigenicity of prostate cancer cells. Free Radical Biology & Medicine. 2012; 53: 95–108. https://doi.org/10.1016/j.freeradbiomed.2012.03.024.
- Google Scholar
[53]Gil M, Rudy M, Stanisławczyk R, Duma-Kocan P, Żurek J. Gender Differences in Eating Habits of Polish Young Adults Aged 20-26. International Journal of Environmental Research and Public Health. 2022; 19: 15280. https://doi.org/10.3390/ijerph192215280.
- Google Scholar

Open Access 24 Apr 2025Original Research

Association of Dietary Antioxidant Potential with Sarcopenia in Hypertension

Yufan Wang ^1,†, Li Liu ^2,†, Shandi Yang ¹, Bingquan Xiong ², Xumin Xin ^2,*

Affiliations

Article Info

¹ Department of Cardiovascular Medicine Intensive Care Unit, The Second Affiliated Hospital of Hainan Medical University, 570311 Haikou, Hainan, China

² Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, 400010 Chongqing, China

^*Correspondence: 302241@hospital.cqmu.edu.cn (Xumin Xin)
^†These authors contributed equally.

Abstract

Background:

The high prevalence of sarcopenia among hypertensive adults is a global health issue. Growing literature demonstrates that a high antioxidant diet can protect against sarcopenia. However, little attention has been paid to the association between the dietary composite antioxidant intake and sarcopenia in hypertension. To investigate the potential efficacy of the composite dietary antioxidant index (CDAI) on sarcopenia among hypertensive adults.

Methods:

This study included 6995 hypertensive adults from the National Health and Nutrition Examination Survey (NHANES) 2001–2006 and 2013–2018, with 3212 (45.92%) females and 3783 (54.08%) males. Appendicular lean mass (ALM) and sarcopenia were assessed by dual-energy X-ray absorptiometry (DEXA). All hypertensive adults participating in NHANES were eligible to participate in dietary interviews, and the average intake of six antioxidants over two days was used to calculate the CDAI. Logistic regression was conducted to determine odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup analyses and restricted cubic spline (RCS) regressions were additionally utilized.

Results:

The mean age was 48.47 ± 0.27 years old, and 1059 (15.14%) were considered to have sarcopenia. The highest quartile had a 61% decreased risk of sarcopenia (OR = 0.39, 95% CI: 0.25, 0.60) compared with the lowest quartile of CDAI. RCS revealed a linear association between CDAI with sarcopenia and ALM. Subgroup analyses demonstrated a more pronounced inverse correlation between CDAI and sarcopenia in females.

Conclusions:

In summary, our results indicated a reverse correlation between CDAI and sarcopenia in hypertension. These findings highlighted the beneficial role of an antioxidant-rich diet in prevention and provided a valid method for managing sarcopenia in hypertensive adults.

Keywords

diet
antioxidant
hypertension
sarcopenia
risk

1. Introduction

Sarcopenia, a chronic condition marked by diminished muscle quality, compromises the quality of life and escalates medical burdens [1]. It is linked to a multitude of diseases. Prominent symptoms include weakness, fatigue, reduced energy, balance impairments, and difficulties with ambulation and standing [2]. A recent study has elucidated the high prevalence of sarcopenia among older adults, notably those with hypertension [3]. Ata and colleagues reported that the incidence of sarcopenia in hypertensive individuals is sixfold higher compared to normotensive counterparts [4]. A large-scale analysis of 15,779 American adults further corroborated that hypertension is intricately linked to an elevated prevalence of sarcopenia [5]. The disparity may be ascribed to the oxidative stress (OS) and chronic inflammation commonly observed in hypertensive patients, both of which are pivotal mechanisms driving the onset of sarcopenia. Additionally, several studies have confirmed that the accumulation of OS and reactive oxygen species (ROS) may contribute to age-related muscle loss [6, 7], while chronic inflammation can disrupt skeletal muscle protein synthesis, thereby increasing the incidence of sarcopenia [8]. Insulin resistance (IR) further influences muscle protein metabolism by interfering with multiple signaling pathways, exacerbating the decline of muscle mass [3]. Thus, effective control of OS, inflammation, and IR in subjects with hypertension may be a potential protective measure to reduce the occurrence of sarcopenia.

Adjusting dietary structure is a valid intervention method that can improve health status by reducing systemic OS levels [9]. Prior research has demonstrated that a higher intake of carotenoids and various vitamins is beneficial in mitigating age-related muscle loss [10]. Combined supplementation of vitamins D and E has been shown to significantly enhance muscle strength in older adults with sarcopenia [11]. A recent study found that adherence to the intake of vitamins A, C, E, and K was linked to a reduced risk of sarcopenia [12]. Another study also showed that increased consumption of dietary microelements had various positive effects on physical performance and decreased the risk of sarcopenia [13]. Conversely, inadequate intake of micronutrients led to diminished antioxidant capacity and declining muscle function [14]. Nevertheless, most previous literature has primarily focused on one or a few nutrients, with little attention given to the impact of overall dietary antioxidant capacity on sarcopenia. The Composite Dietary Antioxidant Index (CDAI) is a reliable assessment tool designed to reflect the total antioxidant capacity (TAC) of individuals, emphasizing the cumulative and synergistic effects of diverse dietary antioxidants [15]. However, few studies have discussed the antioxidant diet impacts on sarcopenia risk in hypertensive individuals. Thus, this study aimed to evaluate the association between CDAI and sarcopenia risk in hypertensive individuals, exploring dose-response relationships and gender differences. To address this knowledge gap, the National Health and Nutrition Examination Survey (NHANES) database was applied in the current research.

2. Materials and Methods

2.1 Study Design

The NHANES is a cross-sectional program established by the National Center for Health Statistics (NCHS) to investigate the prevalence and risk factors of common diseases in the United States. The NHANES protocol was approved by the NCHS Ethics Review Board, obviating the need for additional local ethical approval. On the whole, the data utilized in this analysis is publicly accessible through the NHANES online portal.

Our research leveraged publicly available data from six NHANES cycles (2001–2002, 2003–2004, 2005–2006, 2013–2014, 2015–2016, 2017–2018) to substantiate the true association between CDAI and sarcopenia in hypertension. Specifically, we surveyed 70,655 participants from NHANES 2001–2006 and 2013–2018, initially excluding participants without hypertension (n = 49,772) and those aged less than 20 years old (n = 891). And then, we excluded individuals with missing values for sarcopenia data (n = 10,583), CDAI data (n = 1106) or any other covariates data (n = 1187), and excessive daily energy intake ( $<$ 500 or $>$ 5000 kcal per day) (n = 131). Finally, we analyzed 6995 eligible hypertensive adults in our study (Supplementary Fig. 1).

2.2 Diagnosis of Hypertension

NHANES provided a standardized protocol and procedure for blood pressure measurement. Highly trained examiners conducted three or four blood pressure measurements in mobile examination center (MEC) or during home visits, with participants resting quietly for five minutes before determining the maximum inflation level. To minimize bias, we calculated the average blood pressure to obtain the final blood pressure recording for subsequent statistical analysis [16]. In the current study, hypertension was diagnosed based on self-reported physician diagnoses, a history of antihypertensive medication use, or systolic blood pressure (SBP) $\geq$ 130 mmHg and/or diastolic blood pressure (DBP) $\geq$ 80 mmHg [17].

2.3 Definition of Sarcopenia

The appendicular lean mass (ALM) can be obtained from the NHANES database, which was measured by dual-energy X-ray absorptiometry. Then, the sarcopenia index was obtained by dividing the ALM (kg) by the body mass index (BMI, kg/m²), and sarcopenia was diagnosed based on sex-specific sarcopenia index (cut-off value: 0.512 for females and 0.789 for males) [18].

2.4 Assessment of CDAI

The CDAI consisted of six antioxidants such as vitamins A, C, E, zinc, selenium, and carotenoids. Each antioxidant was standardized by subtracting the total mean and dividing by the total standard deviation (SD). Subsequently, we summarized the standardized intake of individual nutrients according to the formula reported in previous research to derive the CDAI [19]. The detailed calculations can be found in Supplementary Table 1.

2.5 Covariates

According to related research, we considered the following covariates that are associated with sarcopenia: Age, gender, race, marital status, education level, poverty income ratio (PIR) [20], BMI [21], smoking status [22], alcohol consumption [23], cardiovascular disease (CVD), chronic kidney disease (CKD), diabetes [24], uric acid [25], blood urea nitrogen (BUN) [26], white blood cell (WBC) [27], hyperlipidemia [28], and daily energy intake [29] were considered as potential covariates associated with sarcopenia. More details of these covariates are presented in Supplementary Table 2.

2.6 Statistical Analysis

Following the NHANES analysis guidelines, we applied the appropriate sampling weights and accounted for the complex survey design to ensure unbiased estimates in all analyses. Differences in baseline characteristics among the four groups were assessed using one-way analysis of variance (ANOVA) for continuous variables and chi-square tests for categorical variables. Continuous variables were presented as mean $\pm{}$ standard error (SE), and category variables were presented as the frequency with percentage. Logistic regression models were built to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) between CDAI and sarcopenia after adjusting for confounding factors. Likewise, we further explored the relationship between CDAI and ALM using linear regression. Model 1 was an unadjusted crude model. Model 2 was adjusted for age, gender, and race. Model 3 further refined Model 2 by including adjustments for marital status, PIR, education level, BMI, smoking, alcohol use, CVD, CKD, diabetes, uric acid, BUN, WBC, hyperlipidemia, and energy intake. In these models, we converted CDAI from a continuous variable into a categorical variable to verify the CDAI-sarcopenia association. Moreover, a linear trend was tested by entering CDAI as an ordinal variable. Notably, we also assessed the ORs with 95% CIs for each 1-SD increase across different models. To further illustrate the association between sarcopenia, ALM, and CDAI, we conducted restricted cubic spline (RCS) analysis. Notably, the risk of sarcopenia and daily intake of individual antioxidants were also assessed in both minimally adjusted, and fully adjusted models.

Subgroup analyses stratified by age, gender, BMI, diabetes, race, PIR, and alcohol status were performed to investigate the correlation between CDAI and sarcopenia in different populations. The likelihood ratio test was applied to check the interaction among these subgroups.

Additionally, several sensitivity analyses were conducted to assess the robustness of the associations between CDAI and sarcopenia [30]. A new hypertensive cut-off value of 140/90 mmHg was selected to verify the results in the above statistical models. Next, considering that each diagnostic criterion has its advantages and limitations, we used three hypertension diagnosis criteria to verify the correlation between CDAI and sarcopenia risk among hypertensive adults.

Subjects with missing data were excluded from our research. The significance level was set at $\alpha{}$ = 0.05, and all statistical tests were two-tailed. Statistical analyses were performed using R software (version 4.1.3, R Foundation for Statistical Computing, Vienna, Austria).

3. Results

3.1 Baseline Characteristics of the Participants

Table 1 shows the baseline characteristics of the study population stratified by the CDAI quartiles. The study included 6995 hypertensive adults from NHANES 2001–2006 and 2013–2018, with 3212 (45.92%) females and 3783 (54.08%) males. The mean age of enrolled participants was 48.47 $\pm{}$ 0.27 years old, and 1059 (15.14%) were considered to have sarcopenia. Compared with those in the lowest quartile (Q1), participants in the highest quartile (Q4) were more likely to be Non-Hispanic White, college-educated, not-impoverished, married, non-smokers, mild/heavy drinkers, to have a higher energy intake, had lower WBC levels, and had higher BUN levels. Moreover, they were less likely to have CKD, CVD, and sarcopenia. No significant differences were observed in age, gender, uric acid, diabetes, and hyperlipidemia between the four groups at baseline.

Table 1. Characteristics of study participants by CDAI quartiles, weighted (n = 6995) ^𝐚.

Characteristic		Overall	Q1	Q2	Q3	Q4	p value
Sample		6995	1749	1748	1749	1749
Age, years		48.47 $\pm$ 0.27	49.20 $\pm$ 0.52	49.07 $\pm$ 0.48	48.35 $\pm$ 0.45	47.42 $\pm$ 0.49	0.073
Gender, n (%)							0.081
	Female	3212 (45.92)	815 (48.77)	766 (43.80)	785 (42.23)	846 (46.00)
	Male	3783 (54.08)	934 (51.23)	982 (56.20)	964 (57.77)	903 (54.00)
Race, n (%)							0.035
	Mexican American	1117 (15.97)	289 (6.96)	305 (7.63)	267 (7.35)	256 (6.09)
	Non-Hispanic Black	1591 (22.74)	470 (15.45)	380 (11.25)	357 (11.02)	384 (11.17)
	Non-Hispanic White	3278 (46.86)	771 (65.79)	828 (70.81)	843 (69.80)	836 (70.52)
	Other races	1009 (14.42)	219 (11.81)	235 (10.30)	282 (11.82)	273 (12.22)
Education, n (%)							$<$ 0.001
	Less than 9th grade	708 (10.12)	277 (6.53)	179 (4.89)	137 (4.36)	115 (2.43)
	9th–11th grade	951 (13.60)	301 (14.77)	255 (11.38)	205 (9.28)	190 (7.16)
	High school	1708 (24.42)	443 (27.92)	442 (28.61)	430 (24.33)	393 (21.66)
	Some college	2088 (29.85)	504 (32.91)	510 (30.80)	534 (33.41)	540 (31.92)
	College or above	1540 (22.02)	224 (17.88)	362 (24.31)	443 (28.61)	511 (36.82)
PIR, n (%)							$<$ 0.001
	$<$ 1.30	1892 (27.05)	606 (26.20)	479 (19.38)	419 (16.86)	388 (15.57)
	1.30–3.49	2685 (38.38)	701 (39.82)	670 (33.94)	687 (38.19)	627 (31.31)
	$\geq$ 3.50	2418 (34.57)	442 (33.98)	599 (46.68)	643 (44.95)	734 (53.12)
Marital status, n (%)							0.037
	Unmarried	981 (14.02)	241 (14.21)	218 (12.96)	263 (14.30)	259 (14.01)
	Married	3981 (56.91)	935 (55.59)	1015 (60.48)	1002 (58.75)	1029 (63.22)
	Others	2033 (29.06)	573 (30.20)	515 (26.56)	484 (26.94)	461 (22.78)
Energy, kcal/d		2148.82 $\pm$ 19.43	1479.97 $\pm$ 18.68	1948.64 $\pm$ 21.86	2323.33 $\pm$ 25.53	2719.88 $\pm$ 31.24	$<$ 0.001
WBC, 1000 cell/µL		7.44 $\pm$ 0.05	7.59 $\pm$ 0.10	7.49 $\pm$ 0.09	7.50 $\pm$ 0.08	7.23 $\pm$ 0.07	0.004
Uric acid, µmol/L		338.86 $\pm$ 1.44	340.83 $\pm$ 2.99	343.66 $\pm$ 2.70	338.41 $\pm$ 2.92	333.20 $\pm$ 2.96	0.101
BUN, mmol/L		4.82 $\pm$ 0.03	4.60 $\pm$ 0.07	4.82 $\pm$ 0.07	4.85 $\pm$ 0.06	4.98 $\pm$ 0.06	$<$ 0.001
Smoke, n (%)		1550 (22.16)	510 (30.67)	390 (24.42)	363 (22.43)	287 (15.20)	$<$ 0.001
CVD, n (%)		815 (11.65)	254 (10.70)	220 (10.28)	183 (9.03)	158 (7.00)	0.020
CKD, n (%)		1316 (18.81)	410 (19.18)	344 (15.10)	308 (13.85)	254 (11.40)	$<$ 0.001
Diabetes, n (%)		966 (13.81)	253 (10.72)	247 (12.44)	234 (9.66)	232 (9.57)	0.132
Hyperlipidemia, n (%)		5452 (77.94)	1387 (77.32)	1379 (77.78)	1370 (80.47)	1316 (76.99)	0.332
Alcohol status, n (%)							0.012
	Never	906 (12.95)	267 (13.93)	209 (9.66)	215 (9.97)	215 (9.74)
	Former	1269 (18.14)	381 (16.29)	338 (16.28)	272 (14.36)	278 (13.04)
	Mild	2434 (34.80)	508 (31.54)	641 (39.46)	642 (36.75)	643 (37.47)
	Heavy	2386 (34.11)	593 (38.24)	560 (34.61)	620 (38.91)	613 (39.75)
Sarcopenia, n (%)		1059 (15.14)	343 (17.55)	306 (13.63)	228 (10.21)	182 (6.60)	$<$ 0.001

Continuous variables were shown as mean $\pm{}$ SE, categorical variables were shown as frequency (percentage).

^aAll estimates accounted for complex survey designs, and all percentages were weighted.

Q1: CDAI $\leq$ –2.83; Q2: –2.83 $<$ CDAI $\leq$ –0.47; Q3: –0.47 $<$ CDAI $\leq$ 1.87; Q4: CDAI $>$ 1.87.

Abbreviations: Q, quartiles; SE, standard error; CDAI, composite dietary antioxidant index; PIR, poverty income ratio; WBC, white blood cell; BUN, blood urea nitrogen; CVD, cardiovascular disease; CKD, chronic kidney disease.

3.2 Association between CDAI and ALM/Sarcopenia

The associations between CDAI and ALM/sarcopenia are shown in Table 2. Overall, there was an inverse association between CDAI and sarcopenia whereas a positive association between CDAI and ALM in the three statistical models was shown. In the fully adjusted model, the adjusted ORs (95% CIs) were 0.75 (0.57–0.99) for Q2, 0.53 (0.36–0.77) for Q3, and 0.39 (0.25–0.60) for Q4 compared to Q1. Similar results were found when CDAI was treated as a continuous variable. Moreover, eacb 1 SD increase in CDAI was related to a 28% reduced risk of sarcopenia. We further employed multivariable linear regression to explore the relationship between CDAI and ALM. After controlling all confounders, a higher CDAI level was linked to increased ALM, and the corresponding $\beta{}$ (95% CI) of Q4 was 0.54 (0.20, 0.87) when we selected Q1 as the reference. The results of the per 1 SD increase supported our findings in the same model. Importantly, p values for trend were less than 0.05 in the fully adjusted logistic or linear regression models. Additionally, RCS displayed a linear relationship of CDAI with sarcopenia and ALM (both p for non-linearity $>$ 0.050), suggesting a protective effect on sarcopenia at higher CDAI exposure ranges (Fig. 1).

Fig. 1.

Restricted cubic spline (RCS) analysis with multivariate-adjusted association between CDAI and ALM/sarcopenia. (A) RCS analysis between CDAI and sarcopenia risk. (B) RCS analysis between CDAI and ALM risk. Abbreviations: ALM, appendicular lean mass; CDAI, composite dietary antioxidant index.

Table 2. The association between CDAI and sarcopenia risk among hypertensive adults.

Variables			Model 1		Model 2		Model 3
Variables			$\beta$ /OR (95% CI)	p value	$\beta$ /OR (95% CI)	p value	$\beta$ /OR (95% CI)	p value
ALM (kg)
	Continuous		0.10 (0.04, 0.16)	$<$ 0.001	0.12 (0.09, 0.16)	$<$ 0.001	0.06 (0.03, 0.10)	$<$ 0.001
	Categories
		Q1	Reference		Reference		Reference
		Q2	0.95 (0.32, 1.59)	0.004	0.65 (0.26, 1.04)	0.001	0.22 (–0.07, 0.50)	0.137
		Q3	1.41 (0.68, 2.14)	$<$ 0.001	1.03 (0.57, 1.48)	$<$ 0.001	0.34 (0.03, 0.66)	0.032
		Q4	1.38 (0.77, 1.99)	$<$ 0.001	1.36 (0.97, 1.76)	$<$ 0.001	0.54 (0.20, 0.87)	0.002
	p for trend		$<$ 0.001		$<$ 0.001		0.004
	Per 1-SD increase		0.38 (0.16, 0.59)	$<$ 0.001	0.46 (0.31, 0.60)	$<$ 0.001	0.24 (0.12, 0.36)	$<$ 0.001
Sarcopenia
	Continuous		0.89 (0.86, 0.92)	$<$ 0.001	0.89 (0.85, 0.92)	$<$ 0.001	0.92 (0.86, 0.97)	0.003
	Categories
		Q1	Reference		Reference		Reference
		Q2	0.75 (0.60, 0.93)	0.010	0.71 (0.57, 0.88)	0.003	0.75 (0.57, 0.99)	0.043
		Q3	0.55 (0.41, 0.72)	$<$ 0.001	0.51 (0.39, 0.68)	$<$ 0.001	0.53 (0.36, 0.77)	0.001
		Q4	0.35 (0.26, 0.47)	$<$ 0.001	0.34 (0.25, 0.45)	$<$ 0.001	0.39 (0.25, 0.60)	$<$ 0.001
	p for trend		$<$ 0.001		$<$ 0.001		$<$ 0.001
	Per 1-SD increase		0.65 (0.57, 0.75)	$<$ 0.001	0.64 (0.56, 0.74)	$<$ 0.001	0.72 (0.59, 0.89)	0.003

Model 1: Adjusted for age.

Model 2: Adjusted for age, gender, race.

Model 3: Adjusted for age, gender, race, marital status, education level, PIR, BMI, smoke, alcohol status, CVD, CKD, diabetes, uric acid, BUN, WBC, hyperlipidemia, and energy.

Abbreviations: Q, quartiles; CDAI, composite dietary antioxidant index; PIR, poverty income ratio; WBC, white blood cell; BUN, blood urea nitrogen; CVD, cardiovascular disease; CKD, chronic kidney disease; BMI, body mass index; ALM, appendicular lean mass; OR, odds ratio; CI, confidence interval; SD, standard deviation.

3.3 Individual Antioxidant Component and ALM/Sarcopenia

A correlation between specific antioxidant constituents and sarcopenia/ALM were assessed by dividing the value of each individual antioxidant into quartiles, with Q1 selected as the reference category. The detailed results are shown in Table 3. After adjusting all confounding factors, for ALM, the $\beta{}$ (95% CI) comparing Q4 with Q1 was 0.30 (0.01, 0.59) for vitamin A, 0.59 (0.22, 0.95) for vitamin E, 0.35 (0.10, 0.59) for vitamin C, and 0.33 (0.04, 0.62) for carotenoids, respectively. For sarcopenia, inverse associations of sarcopenia with vitamin A, vitamin E, vitamin C, and carotenoids were observed in the fully adjusted model. When comparing with Q1, Q4 of vitamin A, vitamin E, vitamin C, and carotenoids were all linked to a lower risk of sarcopenia among hypertensive adults, with corresponding ORs (95% CIs) of 0.67 (0.47, 0.97), 0.48 (0.31, 0.74), 0.71 (0.48, 0.91), and 0.72 (0.51, 0.92). All p values for the trend in the above regression results were significant. Lastly, the RCS of individual antioxidants and sarcopenia are displayed in Supplementary Fig. 2. We observed that vitamin A, E, and carotenoids were all linearly associated with sarcopenia risk, whereas a non-linear relationship was found between vitamin C and sarcopenia.

Table 3. Multivariable-adjusted regressions according to daily intake of an individual antioxidant component.

		Sarcopenia				ALM (kg)
		Mini-adjusted model		Fully adjusted model		Mini-adjusted model		Fully adjusted model
		OR (95% CI)	p value	OR (95% CI)	p value	$\beta$ (95% CI)	p value	$\beta$ (95% CI)	p value
Vitamin A
	Q1	Reference		Reference		Reference		Reference
	Q2	0.93 (0.70, 1.25)	0.637	1.03 (0.74, 1.43)	0.880	0.80 (0.13, 1.48)	0.019	0.14 (–0.17, 0.46)	0.373
	Q3	0.66 (0.49, 0.89)	0.007	0.78 (0.57, 1.06)	0.115	0.97 (0.31, 1.63)	0.004	0.29 (0.03, 0.54)	0.026
	Q4	0.49 (0.35, 0.67)	$<$ 0.001	0.67 (0.47, 0.97)	0.036	1.47 (0.74, 2.20)	$<$ 0.001	0.30 (0.01, 0.59)	0.044
	p for trend	$<$ 0.001		0.014		$<$ 0.001		0.033
Vitamin E
	Q1	Reference		Reference		Reference		Reference
	Q2	0.67 (0.51, 0.89)	0.007	0.80 (0.57, 1.10)	0.168	1.02 (0.44, 1.60)	$<$ 0.001	0.26 (–0.04, 0.56)	0.091
	Q3	0.63 (0.47, 0.84)	0.002	0.76 (0.54, 1.08)	0.126	1.70 (1.12, 2.28)	$<$ 0.001	0.31 (0.04, 0.58)	0.024
	Q4	0.39 (0.28, 0.53)	$<$ 0.001	0.48 (0.31, 0.74)	0.001	3.21 (2.57, 3.86)	$<$ 0.001	0.59 (0.22, 0.95)	0.002
	p for trend	$<$ 0.001		0.003		$<$ 0.001		0.006
Vitamin C
	Q1	Reference		Reference		Reference		Reference
	Q2	0.95 (0.76, 1.19)	0.643	1.15 (0.87, 1.52)	0.334	0.59 (–0.09, 1.28)	0.086	0.10 (–0.15, 0.36)	0.428
	Q3	0.62 (0.45, 0.84)	0.002	0.75 (0.54, 0.86)	0.024	0.99 (0.44, 1.54)	$<$ 0.001	0.35 (0.08, 0.62)	0.012
	Q4	0.57 (0.41, 0.78)	$<$ 0.001	0.71 (0.48, 0.91)	0.026	1.17 (0.61, 1.72)	$<$ 0.001	0.35 (0.10, 0.59)	0.006
	p for trend	$<$ 0.001		0.023		$<$ 0.001		0.002
ZinC
	Q1	Reference		Reference		Reference		Reference
	Q2	1.05 (0.79, 1.41)	0.717	1.06 (0.75, 1.48)	0.745	1.35 (0.76, 1.94)	$<$ 0.001	–0.02 (–0.30, 0.26)	0.872
	Q3	0.76 (0.52, 1.12)	0.163	0.83 (0.53, 1.31)	0.424	2.82 (2.26, 3.38)	$<$ 0.001	0.01 (–0.33, 0.35)	0.940
	Q4	0.62 (0.45, 0.87)	0.006	0.66 (0.40, 1.08)	0.100	4.69 (4.07, 5.31)	$<$ 0.001	0.28 (–0.09, 0.65)	0.141
	p for trend	0.003		0.075		$<$ 0.001		0.187
Selenium
	Q1	Reference		Reference		Reference		Reference
	Q2	0.72 (0.52, 1.00)	0.047	0.68 (0.47, 0.99)	0.045	1.42 (0.90, 1.94)	$<$ 0.001	–0.06 (–0.32, 0.21)	0.675
	Q3	0.73 (0.54, 1.01)	0.054	0.74 (0.49, 1.11)	0.140	3.31 (2.77, 3.84)	$<$ 0.001	–0.09 (–0.39, 0.22)	0.559
	Q4	0.59 (0.44, 0.79)	$<$ 0.001	0.66 (0.43, 1.03)	0.064	5.19 (4.55, 5.84)	$<$ 0.001	0.34 (–0.05, 0.73)	0.085
	p for trend	0.001		0.107		$<$ 0.001		0.141
Carotenoids
	Q1	Reference		Reference		Reference		Reference
	Q2	0.99 (0.75, 1.29)	0.920	0.97 (0.70, 1.35)	0.863	0.17 (–0.38, 0.72)	0.545	0.07 (–0.22, 0.36)	0.647
	Q3	0.92 (0.69, 1.22)	0.571	0.92 (0.66, 1.27)	0.593	0.5 (–0.13, 1.13)	0.119	0.18 (–0.10, 0.46)	0.200
	Q4	0.61 (0.45, 0.82)	0.001	0.72 (0.51, 0.92)	0.033	1.02 (0.42, 1.61)	0.001	0.33 (0.04, 0.62)	0.025
	p for trend	0.002		0.039		0.001		0.017

Mini-adjusted model: Adjusted for age.

Fully-adjusted model: Adjusted for age, gender, race, marital status, education level, PIR, BMI, smoke, alcohol status, CVD, CKD, diabetes, uric acid, BUN, WBC, hyperlipidemia and energy.

Abbreviations: Q, quartiles; PIR, poverty income ratio; WBC, white blood cell; BUN, blood urea nitrogen; CVD, cardiovascular disease; CKD, chronic kidney disease; BMI, body mass index; ALM, appendicular lean mass; OR, odds ratio; CI, confidence interval.

3.4 Subgroup and Sensitivity Analysis

Subgroup analyses stratified by age, gender, BMI, diabetes, race, PIR, and alcohol consumption were performed (Fig. 2). The results indicated that a relatively stronger association between CDAI and sarcopenia among hypertensive adults was found among females, and a significant interaction was observed (p interaction $<$ 0.050). In the sensitivity analyses, we initially selected 140/90 mmHg as the hypertensive cut-off value to explore the correlation between CDAI and sarcopenia among hypertensive adults. As expected, we found the results were robust by using logistic and linear regression (Supplementary Table 3). Next, our result consistently demonstrated that CDAI was related to a decreased risk of sarcopenia among hypertensive adults by using three different hypertension diagnosis criteria (Supplementary Table 4).

Fig. 2.

Subgroup analysis of the association between CDAI and sarcopenia. Abbreviations: CDAI, composite dietary antioxidant index; PIR, poverty income ratio; OR, odds ratio; CI, confidence interval; BMI, body mass index.

4. Discussion

The present research demonstrated an inverse correlation between CDAI and sarcopenia in hypertensive patients, suggeting a protective effect of CDAI against the progression of sarcopenia, particularly in females. The RCS analysis further indicated a linear trend between CDAI and sarcopenia, suggesting the risk of sarcopenia decreased as CDAI increased. These results underscore the benefits of a diet rich in antioxidants for hypertensive patients in preventing the onset of sarcopenia.

Our results showed that high intake of the antioxidant-rich diet confered a reduced risk of sarcopenia in hypertensive patients, supported by several prior studies. Two large population-based studies have established that adequate vitamin C intake provides protection against sarcopenia [31, 32]. Meanwhile, an observational study by Mulligan et al. [33] suggested that consuming more vitamin E is beneficial for musculoskeletal health. Another survey of 1345 participants also discovered an inverse correlation between vitamin E intake and sarcopenia, further demonstrating the advantages of dietary antioxidants for sarcopenia [34]. Additionally, a prospective cohort study data from two community-based cohorts demonstrated that the intake of antioxidant nutrients, particularly carotenoids, is positively related to grip strength and gait speed in elderly individuals, highlighting the impact of an antioxidant diet on muscle mass and physical performance [35]. A previous study also showed that nutritional intervention with antioxidants could enhance muscle mass in antioxidant-deficient mice, indicating that the adverse effects of antioxidant insufficiency can be mitigated by supplementation [36]. Therefore, individuals with high levels of OS, especially hypertensive patients, should modify their dietary patterns to increase CDAI levels to prevent sarcopenia.

Our findings revealed that the risk of skeletal sarcopenia decreased with increasing CDAI in the hypertensive population. Multicenter clinical research involving 2613 participants concluded that hypertension, a chronic age-related metabolic disorder, can lead to diminished muscle function and an elevated risk of sarcopenia [37]. Hypertension is often accompanied by prolonged OS, which can result in muscle injury and disordered muscle protein metabolism [36, 38]. With age, the body’s endogenous antioxidant defence system declines and the excessive accumulation of ROS contributes to oxidative muscle damage. Additionally, mitochondrial dysfunction becomes prominent during muscle aging, a phenomenon linked to dysregulated ROS production and subsequent oxidative damage [39]. Many dietary antioxidants mitigate OS through their bioactive molecules, by integrating metabolic processes, and by regulating gene expression as cellular signaling modulators [40]. Prior literature performed by van Dijk et al. [36] demonstrated that supplementation with dietary antioxidants improved mitochondrial dynamics, thereby protecting and enhancing muscle strength and mass in aged mice with antioxidant deficiencies. The maintenance of muscle mass depends on the balance between protein synthesis and degradation [41]. This balance can be disrupted by OS, which accelerates protein degradation and inhibits protein synthesis, thereby promoting skeletal muscle atrophy [36]. OS-related impairment of muscle mass in older adults can be mitigated by antioxidant-rich foods [42]. Several vitamins and carotenoids can improve muscle mass by increasing protein and collagen synthesis while protecting muscles from OS and inflammation [10]. Several studies have already revealed that higher intake of antioxidants, such as carotenoids, vitamin C and E are related to skeletal muscle health [10, 11]. The benefits of healthy dietary patterns in reducing the sarcopenia risk were confirmed in a population-based study of older adults [43]. Micronutrient-rich fruits and vegetables can prevent metabolic acidosis, reduce protein hydrolysis, and decrease amino acid catabolism, thereby contributing to muscle quality and function [44]. In addition, dietary zinc and selenium are also important micronutrients that play a crucial role in combating oxidation; however, high concentrations of these elements can induce toxic and oxidative effects and inhibit antioxidant enzymes [45, 46]. Notably, numerous reports have highlighted that chronic inflammation and IR are also crucial components in the mechanism of sarcopenia. A prior observational study by Luu et al. [47] exhibited that CDAI was inversely related to levels of multiple inflammatory biomarkers. Another published research article indicated a reverse correlation between dietary TAC and IR, suggesting the potential effect of an antioxidant diet on improving insulin sensitivity [48]. Therefore, we speculated that adherence to an antioxidant-rich diet may confer potential benefits in improving muscle mass by eliminating the deleterious impacts of chronic inflammation and IR in hypertensive individuals, thereby reducing the risk of sarcopenia.

However, prior research has predominantly focused on the isolated effects of individual antioxidants on muscle mass, neglecting to fully explore the potential interactions and synergistic effects among different antioxidants. The CDAI provides a comprehensive evaluation of an individual’s overall antioxidant intake by combining various dietary components, including vitamins, and other antioxidants. This integrated approach reflects the combined effects of multiple antioxidants in the diet, rather than focusing on a single nutrient. CDAI mitigates potential biases and errors inherent in single nutrient studies by integrating the effects of multiple antioxidants, thereby enhancing the reliability of the results. CDAI offers a more accurate reflection of antioxidant intake in daily diets, while individual antioxidants are typically confined to specific foods or supplements.

According to our subgroup analysis, it was noted that an inverse association of CDAI and sarcopenia was found only in females but not males. This phenomenon may be owing to the distinctions in endogenous sex hormones. Estrogen, a hormone predominantly found in females, is known to have an antioxidant-like impact, by reducing ROS production and stimulating the upregulation of genes encoding antioxidant enzymes [49, 50]. Moreover, estrogens contain phenol hydroxyl and methyl groups, which confer antioxidant properties by scavenging oxygen free radicals [51]. Conversely, androgens, which are predominantly found in males, are known to induce OS by facilitating the generation of ROS, significantly diminishing the benefits of an antioxidant-rich diet on muscle health in men [52]. More importantly, females generally exhibit superior dietary habits compared to males, consuming more micronutrient-rich foods such as fruits and vegetables, and employing healthier cooking and processing methods [53]. Thus, females with hypertension may derive more benefit from a high antioxidant diet than males with hypertension.

Our research has several strengths. Firstly, our data was established from the NHANES database, a large-scale national investigation, which helped ensure the reliability of our results. Secondly, by counting dietary CDAI, our research firstly clarified the negative correlation between sarcopenia and overall dietary antioxidant capacity in hypertensive individuals, revealing that higher CDAI serves as a protective factor against sarcopenia. Thirdly, the stability of our results was confirmed by sensitivity analyses performed by different approaches.

However, several limitations of our research should also be considered. Firstly, given the cross-sectional nature of the data, the causal effect cannot be established between CDAI and sarcopenia. Secondly, since the NHANES data did not distinguish between primary and secondary sarcopenia, and the diagnosis was based solely on muscle mass without incorporating grip strength, which may limit the generalizability of our findings to all types of sarcopenia. Thirdly, dietary data was collected through 24 hour recall interviews, which might lead to recall bias and may not accurately reflect the actual dietary intake. Additionally, the 24 hour dietary recall method may not capture habitual dietary patterns, introducing potential measurement biases in the dietary assessment. Fourthly, the CDAI was calculated based solely on baseline dietary data, which may not accurately reflect long-term dietary patterns. Moreover, the singular diagnostic criterion for sarcopenia based solely on muscle mass without considering muscle strength or physical performance may limit the generalizability of the results. Finally, despite adjusting for known conventional variables, there may still be unmeasured confounders that could affect our results, such as physical activity levels and chronic disease burden, which were not accounted for in our analysis. Future prospective cohort studies are required to shed more light on our results.

5. Conclusions

The present study, based on data from NHANES, detected an inverse connection between CDAI and sarcopenia in hypertensive adults, suggesting that an antioxidant-rich diet may offer a beneficial impact and serve as an effective method of preventing sarcopenia for hypertensive patients.

Availability of Data and Materials

Data described in the manuscript are publicly and freely available without restriction at https://www.cdc.gov/nchs/nhanes/index.htm.

Author Contributions

YW and LL had the main responsibility for data analysis and writing the manuscript. SY and BX assisted with data analysis and revised the manuscript. XX designed the study, supervised the entire study, revised the manuscript, and provided the overall theme and direction. Additionally, XX contributed significantly to the intellectual content of the manuscript, ensuring its alignment with the study’s objectives. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

Ethics Approval and Consent to Participate

NHANES is conducted by the Centers for Disease Control and Prevention (CDC) and the National Center for Health Statistics (NCHS). The related research was carried out in accordance with the guidelines of the Declaration of Helsinki. The NCHS Research Ethics Review Committee reviewed and approved the NHANES study protocol. All participants signed written informed consent.

Acknowledgment

We thank the NHANES staff for their excellent work on study design and data collection.

Funding

This research received no external funding.

Conflict of Interest

The authors declare no conflict of interest.

Supplementary Material

Supplementary material associated with this article can be found, in the online version, at https://doi.org/10.31083/RCM27138.

References

[1] Jimenez-Gutierrez GE, Martínez-Gómez LE, Martínez-Armenta C, Pineda C, Martínez-Nava GA, Lopez-Reyes A. Molecular Mechanisms of Inflammation in Sarcopenia: Diagnosis and Therapeutic Update. Cells. 2022; 11: 2359. https://doi.org/10.3390/cells11152359.
Cited within: 1Google Scholar Crossref
[2] Tarantino G, Sinatti G, Citro V, Santini SJ, Balsano C. Sarcopenia, a condition shared by various diseases: can we alleviate or delay the progression? Internal and Emergency Medicine. 2023; 18: 1887–1895. https://doi.org/10.1007/s11739-023-03339-z.
Cited within: 1Google Scholar Crossref
[3] Xing E, Wan C. Prevalence of and factors associated with sarcopenia among elderly individuals with hypertension. The Journal of International Medical Research. 2022; 50: 3000605221110490. https://doi.org/10.1177/03000605221110490.
Cited within: 2Google Scholar Crossref
[4] Ata AM, Kara M, Ekiz T, Kara Ö, Culha MA, Ricci V, et al. Reassessing Sarcopenia in Hypertension: STAR and ACE Inhibitors Excel. International Journal of Clinical Practice. 2021; 75: e13800. https://doi.org/10.1111/ijcp.13800.
Cited within: 1Google Scholar Crossref
[5] Li M, Ji R, Liu X, Wu Y. Associations of metabolic syndrome and its components with sarcopenia, and the mediating role of insulin resistance: Findings from NHANES database. BMC Endocrine Disorders. 2024; 24: 203. https://doi.org/10.1186/s12902-024-01736-9.
Cited within: 1Google Scholar Crossref
[6] Can B, Kara O, Kizilarslanoglu MC, Arik G, Aycicek GS, Sumer F, et al. Serum markers of inflammation and oxidative stress in sarcopenia. Aging Clinical and Experimental Research. 2017; 29: 745–752. https://doi.org/10.1007/s40520-016-0626-2.
Cited within: 1Google Scholar Crossref
[7] Sinha-Hikim I, Sinha-Hikim AP, Parveen M, Shen R, Goswami R, Tran P, et al. Long-term supplementation with a cystine-based antioxidant delays loss of muscle mass in aging. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences. 2013; 68: 749–759. https://doi.org/10.1093/gerona/gls334.
Cited within: 1Google Scholar Crossref
[8] Diao H, Yan F, He Q, Li M, Zheng Q, Zhu Q, et al. Association between Dietary Inflammatory Index and Sarcopenia: A Meta-Analysis. Nutrients. 2023; 15: 219. https://doi.org/10.3390/nu15010219.
Cited within: 1Google Scholar Crossref
[9] Chen Y, Tang W, Li H, Lv J, Chang L, Chen S. Composite dietary antioxidant index negatively correlates with osteoporosis among middle-aged and older US populations. American Journal of Translational Research. 2023; 15: 1300–1308.
Cited within: 1Google Scholar Crossref
[10] Welch AA, Jennings A, Kelaiditi E, Skinner J, Steves CJ. Cross-Sectional Associations Between Dietary Antioxidant Vitamins C, E and Carotenoid Intakes and Sarcopenic Indices in Women Aged 18-79 Years. Calcified Tissue International. 2020; 106: 331–342. https://doi.org/10.1007/s00223-019-00641-x.
Cited within: 3Google Scholar Crossref
[11] Bo Y, Liu C, Ji Z, Yang R, An Q, Zhang X, et al. A high whey protein, vitamin D and E supplement preserves muscle mass, strength, and quality of life in sarcopenic older adults: A double-blind randomized controlled trial. Clinical Nutrition (Edinburgh, Scotland). 2019; 38: 159–164. https://doi.org/10.1016/j.clnu.2017.12.020.
Cited within: 2Google Scholar Crossref
[12] Liu Y, Liu X, Duan L, Zhao Y, He Y, Li W, et al. Associations of micronutrient dietary patterns with sarcopenia among US adults: a population-based study. Frontiers in Nutrition. 2024; 11: 1301831. https://doi.org/10.3389/fnut.2024.1301831.
Cited within: 1Google Scholar Crossref
[13] van Dronkelaar C, van Velzen A, Abdelrazek M, van der Steen A, Weijs PJM, Tieland M. Minerals and Sarcopenia; The Role of Calcium, Iron, Magnesium, Phosphorus, Potassium, Selenium, Sodium, and Zinc on Muscle Mass, Muscle Strength, and Physical Performance in Older Adults: A Systematic Review. Journal of the American Medical Directors Association. 2018; 19: 6–11.e3. https://doi.org/10.1016/j.jamda.2017.05.026.
Cited within: 1Google Scholar Crossref
[14] van Dijk M, Dijk FJ, Hartog A, van Norren K, Verlaan S, van Helvoort A, et al. Reduced dietary intake of micronutrients with antioxidant properties negatively impacts muscle health in aged mice. Journal of Cachexia, Sarcopenia and Muscle. 2018; 9: 146–159. https://doi.org/10.1002/jcsm.12237.
Cited within: 1Google Scholar Crossref
[15] Wang L, Yi Z. Association of the Composite dietary antioxidant index with all-cause and cardiovascular mortality: A prospective cohort study. Frontiers in Cardiovascular Medicine. 2022; 9: 993930. https://doi.org/10.3389/fcvm.2022.993930.
Cited within: 1Google Scholar Crossref
[16] Miao H, Liu Y, Tsai TC, Schwartz J, Ji JS. Association Between Blood Lead Level and Uncontrolled Hypertension in the US Population (NHANES 1999-2016). Journal of the American Heart Association. 2020; 9: e015533. https://doi.org/10.1161/JAHA.119.015533.
Cited within: 1Google Scholar Crossref
[17] Whelton PK, Carey RM, Aronow WS, Casey DE, Jr, Collins KJ, Dennison Himmelfarb C, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension. 2018; 71: e13–e115. https://doi.org/10.1161/HYP.0000000000000065.
Cited within: 1Google Scholar Crossref
[18] Chen W, Shi S, Jiang Y, Chen K, Liao Y, Huang R, et al. Association of sarcopenia with ideal cardiovascular health metrics among US adults: a cross-sectional study of NHANES data from 2011 to 2018. BMJ Open. 2022; 12: e061789. https://doi.org/10.1136/bmjopen-2022-061789.
Cited within: 1Google Scholar Crossref
[19] Maugeri A, Hruskova J, Jakubik J, Kunzova S, Sochor O, Barchitta M, et al. Dietary antioxidant intake decreases carotid intima media thickness in women but not in men: A cross-sectional assessment in the Kardiovize study. Free Radical Biology & Medicine. 2019; 131: 274–281. https://doi.org/10.1016/j.freeradbiomed.2018.12.018.
Cited within: 1Google Scholar
[20] Dai S, Shu D, Meng F, Chen Y, Wang J, Liu X, et al. Higher Risk of Sarcopenia in Older Adults with Type 2 Diabetes: NHANES 1999-2018. Obesity Facts. 2023; 16: 237–248. https://doi.org/10.1159/000530241.
Cited within: 1Google Scholar Crossref
[21] Yu B, Sun Y, Du X, Zhang H, Chen C, Tan X, et al. Age-specific and sex-specific associations of visceral adipose tissue mass and fat-to-muscle mass ratio with risk of mortality. Journal of Cachexia, Sarcopenia and Muscle. 2023; 14: 406–417. https://doi.org/10.1002/jcsm.13142.
Cited within: 1Google Scholar Crossref
[22] Rom O, Kaisari S, Aizenbud D, Reznick AZ. Sarcopenia and smoking: a possible cellular model of cigarette smoke effects on muscle protein breakdown. Annals of the New York Academy of Sciences. 2012; 1259: 47–53. https://doi.org/10.1111/j.1749-6632.2012.06532.x.
Cited within: 1Google Scholar Crossref
[23] Bu YL, Wang C, Zhao C, Lu X, Gao W. The association of alcohol consumption with the risk of sarcopenia: a dose-response meta-analysis. The American Journal of Drug and Alcohol Abuse. 2024; 50: 305–320. https://doi.org/10.1080/00952990.2023.2300049.
Cited within: 1Google Scholar Crossref
[24] Izzo A, Massimino E, Riccardi G, Della Pepa G. A Narrative Review on Sarcopenia in Type 2 Diabetes Mellitus: Prevalence and Associated Factors. Nutrients. 2021; 13: 183. https://doi.org/10.3390/nu13010183.
Cited within: 1Google Scholar Crossref
[25] Zhou S, Wu L, Si H, Shen B. Longitudinal Association between Uric Acid and Incident Sarcopenia. Nutrients. 2023; 15: 3097. https://doi.org/10.3390/nu15143097.
Cited within: 1Google Scholar Crossref
[26] Gao H, Wang J, Zou X, Zhang K, Zhou J, Chen M. High blood urea nitrogen to creatinine ratio is associated with increased risk of sarcopenia in patients with chronic obstructive pulmonary disease. Experimental Gerontology. 2022; 169: 111960. https://doi.org/10.1016/j.exger.2022.111960.
Cited within: 1Google Scholar Crossref
[27] Lee HS, Koh IH, Kim HS, Kwon YJ. Platelet and white blood cell count are independently associated with sarcopenia: A nationwide population-based study. Thrombosis Research. 2019; 183: 36–44. https://doi.org/10.1016/j.thromres.2019.09.007.
Cited within: 1Google Scholar Crossref
[28] Lin MH, Chiu SY, Chang PH, Lai YL, Chen PC, Ho WC. Hyperlipidemia and Statins Use for the Risk of New Diagnosed Sarcopenia in Patients with Chronic Kidney: A Population-Based Study. International Journal of Environmental Research and Public Health. 2020; 17: 1494. https://doi.org/10.3390/ijerph17051494.
Cited within: 1Google Scholar Crossref
[29] Kim H, Yoo S, Park YS, Park SG. Low dietary energy intake is associated with sarcopenia in cancer survivors: An analysis based on the Korean National Health and Nutrition Examination Survey 2008-2011. Nutrition Research. 2018; 53: 15–22. https://doi.org/10.1016/j.nutres.2018.01.004.
Cited within: 1Google Scholar Crossref
[30] Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL, Jr, et al. Seventh report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure. Hypertension. 2003; 42: 1206–1252. https://doi.org/10.1161/01.HYP.0000107251.49515.c2.
Cited within: 1Google Scholar Crossref
[31] Lewis LN, Hayhoe RPG, Mulligan AA, Luben RN, Khaw KT, Welch AA. Lower Dietary and Circulating Vitamin C in Middle- and Older-Aged Men and Women Are Associated with Lower Estimated Skeletal Muscle Mass. The Journal of Nutrition. 2020; 150: 2789–2798. https://doi.org/10.1093/jn/nxaa221.
Cited within: 1Google Scholar Crossref
[32] Abete I, Konieczna J, Zulet MA, Galmés-Panades AM, Ibero-Baraibar I, Babio N, et al. Association of lifestyle factors and inflammation with sarcopenic obesity: data from the PREDIMED-Plus trial. Journal of Cachexia, Sarcopenia and Muscle. 2019; 10: 974–984. https://doi.org/10.1002/jcsm.12442.
Cited within: 1Google Scholar Crossref
[33] Mulligan AA, Hayhoe RPG, Luben RN, Welch AA. Positive Associations of Dietary Intake and Plasma Concentrations of Vitamin E with Skeletal Muscle Mass, Heel Bone Ultrasound Attenuation and Fracture Risk in the EPIC-Norfolk Cohort. Antioxidants. 2021; 10: 159. https://doi.org/10.3390/antiox10020159.
Cited within: 1Google Scholar Crossref
[34] Otsuka Y, Iidaka T, Horii C, Muraki S, Oka H, Nakamura K, et al. Dietary Intake of Vitamin E and Fats Associated with Sarcopenia in Community-Dwelling Older Japanese People: A Cross-Sectional Study from the Fifth Survey of the ROAD Study. Nutrients. 2021; 13: 1730. https://doi.org/10.3390/nu13051730.
Cited within: 1Google Scholar Crossref
[35] Sahni S, Dufour AB, Fielding RA, Newman AB, Kiel DP, Hannan MT, et al. Total carotenoid intake is associated with reduced loss of grip strength and gait speed over time in adults: The Framingham Offspring Study. The American Journal of Clinical Nutrition. 2021; 113: 437–445. https://doi.org/10.1093/ajcn/nqaa288.
Cited within: 1Google Scholar Crossref
[36] van Dijk M, Dijk FJ, Bunschoten A, van Dartel DAM, van Norren K, Walrand S, et al. Improved muscle function and quality after diet intervention with leucine-enriched whey and antioxidants in antioxidant deficient aged mice. Oncotarget. 2016; 7: 17338–17355. https://doi.org/10.18632/oncotarget.7800.
Cited within: 4Google Scholar Crossref
[37] Kara M, Kara Ö, Ceran Y, Kaymak B, Kaya TC, Çıtır BN, et al. SARcopenia Assessment in Hypertension: The SARAH Study. American Journal of Physical Medicine & Rehabilitation. 2023; 102: 130–136. https://doi.org/10.1097/PHM.0000000000002045.
Cited within: 1Google Scholar
[38] Griendling KK, Camargo LL, Rios FJ, Alves-Lopes R, Montezano AC, Touyz RM. Oxidative Stress and Hypertension. Circulation Research. 2021; 128: 993–1020. https://doi.org/10.1161/CIRCRESAHA.121.318063.
Cited within: 1Google Scholar Crossref
[39] Liu S, Zhang L, Li S. Advances in nutritional supplementation for sarcopenia management. Frontiers in Nutrition. 2023; 10: 1189522. https://doi.org/10.3389/fnut.2023.1189522.
Cited within: 1Google Scholar Crossref
[40] Zhao L, Sun Y, Cao R, Wu X, Huang T, Peng W. Non-linear association between composite dietary antioxidant index and depression. Frontiers in Public Health. 2022; 10: 988727. https://doi.org/10.3389/fpubh.2022.988727.
Cited within: 1Google Scholar Crossref
[41] Cuthbertson D, Smith K, Babraj J, Leese G, Waddell T, Atherton P, et al. Anabolic signaling deficits underlie amino acid resistance of wasting, aging muscle. FASEB Journal: Official Publication of the Federation of American Societies for Experimental Biology. 2005; 19: 422–424. https://doi.org/10.1096/fj.04-2640fje.
Cited within: 1Google Scholar Crossref
[42] Baharirad N, Pasdar Y, Nachvak M, Ghavamzadeh S, Soroush A, Saber A, et al. The relationship of dietary total antioxidant capacity with sarcopenia and cardiometabolic biomarkers in type 2 diabetes patients. Physiological Reports. 2022; 10: e15190. https://doi.org/10.14814/phy2.15190.
Cited within: 1Google Scholar Crossref
[43] Papaioannou KG, Nilsson A, Nilsson LM, Kadi F. Healthy Eating Is Associated with Sarcopenia Risk in Physically Active Older Adults. Nutrients. 2021; 13: 2813. https://doi.org/10.3390/nu13082813.
Cited within: 1Google Scholar Crossref
[44] Kim J, Lee Y, Kye S, Chung YS, Kim KM. Association of vegetables and fruits consumption with sarcopenia in older adults: the Fourth Korea National Health and Nutrition Examination Survey. Age and Ageing. 2015; 44: 96–102. https://doi.org/10.1093/ageing/afu028.
Cited within: 1Google Scholar Crossref
[45] Barragán R, Sánchez-González C, Aranda P, Sorlí JV, Asensio EM, Portolés O, et al. Single and Combined Associations of Plasma and Urine Essential Trace Elements (Zn, Cu, Se, and Mn) with Cardiovascular Risk Factors in a Mediterranean Population. Antioxidants. 2022; 11: 1991. https://doi.org/10.3390/antiox11101991.
Cited within: 1Google Scholar Crossref
[46] Wang S, Nong X, Yang G. Selenium-Rich Diet Induces Myocardial Structural and Functional Abnormalities by Activating Caspase-9 and Caspase-3 in Gpx-1P198L-Overexpression Transgenic Mice. Medical Science Monitor. 2019; 25: 61–70. https://doi.org/10.12659/MSM.911120.
Cited within: 1Google Scholar Crossref
[47] Luu HN, Wen W, Li H, Dai Q, Yang G, Cai Q, et al. Are dietary antioxidant intake indices correlated to oxidative stress and inflammatory marker levels? Antioxidants & Redox Signaling. 2015; 22: 951–959. https://doi.org/10.1089/ars.2014.6212.
Cited within: 1Google Scholar
[48] Galarregui C, Zulet MÁ, Cantero I, Marín-Alejandre BA, Monreal JI, Elorz M, et al. Interplay of Glycemic Index, Glycemic Load, and Dietary Antioxidant Capacity with Insulin Resistance in Subjects with a Cardiometabolic Risk Profile. International Journal of Molecular Sciences. 2018; 19: 3662. https://doi.org/10.3390/ijms19113662.
Cited within: 1Google Scholar Crossref
[49] Kanno SI, Tomizawa A, Yomogida S, Hara A. Glutathione peroxidase 3 is a protective factor against acetaminophen induced hepatotoxicity in vivo and in vitro. International Journal of Molecular Medicine. 2017; 40: 748–754. https://doi.org/10.3892/ijmm.2017.3049.
Cited within: 1Google Scholar Crossref
[50] Viña J, Borrás C, Gambini J, Sastre J, Pallardó FV. Why females live longer than males? Importance of the upregulation of longevity-associated genes by oestrogenic compounds. FEBS Letters. 2005; 579: 2541–2545. https://doi.org/10.1016/j.febslet.2005.03.090.
Cited within: 1Google Scholar Crossref
[51] Barp J, Araújo ASR, Fernandes TRG, Rigatto KV, Llesuy S, Belló-Klein A, et al. Myocardial antioxidant and oxidative stress changes due to sex hormones. Brazilian Journal of Medical and Biological Research. 2002; 35: 1075–1081. https://doi.org/10.1590/s0100-879x2002000900008.
Cited within: 1Google Scholar Crossref
[52] Veeramani S, Chou YW, Lin FC, Muniyan S, Lin FF, Kumar S, et al. Reactive oxygen species induced by p66Shc longevity protein mediate nongenomic androgen action via tyrosine phosphorylation signaling to enhance tumorigenicity of prostate cancer cells. Free Radical Biology & Medicine. 2012; 53: 95–108. https://doi.org/10.1016/j.freeradbiomed.2012.03.024.
Cited within: 1Google Scholar
[53] Gil M, Rudy M, Stanisławczyk R, Duma-Kocan P, Żurek J. Gender Differences in Eating Habits of Polish Young Adults Aged 20-26. International Journal of Environmental Research and Public Health. 2022; 19: 15280. https://doi.org/10.3390/ijerph192215280.
Cited within: 1Google Scholar Crossref

Publisher’s Note: IMR Press stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Academic Editor

Download

Fig. 1.

Fig. 2.

Academic Editor

Article Metrics

Download

Fig. 1.

Fig. 2.

Abstract

Keywords

References