Yamanaka Y (2020) Basic concepts and unique features of human circadian rhythms: implications for human health. Nutr Rev 78(Suppl 3):91–96. https://doi.org/10.1093/nutrit/nuaa072

Article  PubMed  Google Scholar 

Montaruli A, Castelli L, Mule A et al (2021) Biological rhythm and chronotype: new perspectives in health. Biomolecules 11:487. https://doi.org/10.3390/biom11040487

Article  CAS  PubMed  PubMed Central  Google Scholar 

Xie Y, Tang Q, Chen G et al (2019) New insights into the circadian rhythm and its related diseases. Front Physiol 10:682. https://doi.org/10.3389/fphys.2019.00682

Article  PubMed  PubMed Central  Google Scholar 

Abbott SM, Malkani RG, Zee PC (2020) Circadian disruption and human health: a bidirectional relationship. Eur J Neurosci 51:567–583. https://doi.org/10.1111/ejn.14298

Article  PubMed  Google Scholar 

Foster RG (2020) Sleep, circadian rhythms and health. Interface Focus 10:20190098. https://doi.org/10.1098/rsfs.2019.0098

Article  PubMed  PubMed Central  Google Scholar 

Farhud D, Aryan Z (2018) Circadian rhythm, lifestyle and health: a narrative review. Iran J Public Health 47:1068–1076

PubMed  PubMed Central  Google Scholar 

Fishbein AB, Knutson KL, Zee PC (2021) Circadian disruption and human health. J Clin Invest 131:e148286. https://doi.org/10.1172/JCI148286

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hower IM, Harper SA, Buford TW (2018) Circadian rhythms, exercise, and cardiovascular health. J Circadian Rhythms 16:7. https://doi.org/10.5334/jcr.164

Article  PubMed  PubMed Central  Google Scholar 

Öney B, Balcı Ç (2021) Sirkadiyen ritmin sağlıktaki rolü. Turk Saglik Bilim Arast Derg 4:64–75. https://doi.org/10.51536/tusbad.922995

Article  Google Scholar 

Jagannath A, Taylor L, Wakaf Z et al (2017) The genetics of circadian rhythms, sleep and health. Hum Mol Genet 26:R128–R138. https://doi.org/10.1093/hmg/ddx240

Article  CAS  PubMed  PubMed Central  Google Scholar 

Poggiogalle E, Jamshed H, Peterson CM (2018) Circadian regulation of glucose, lipid, and energy metabolism in humans. Metabolism 84:11–27. https://doi.org/10.1016/j.metabol.2017.11.017

Article  CAS  PubMed  PubMed Central  Google Scholar 

Gentry NW, Ashbrook LH, Fu Y et al (2021) Human circadian variations. J Clin Invest 131:e148282. https://doi.org/10.1172/JCI148282

Article  CAS  PubMed  PubMed Central  Google Scholar 

Lu C, Zong J, Wang L et al (2022) Healthy aging index and its link with relative education between individual and neighborhood: a population-based, cohort study. BMC Geriatr 22:778. https://doi.org/10.1186/s12877-022-03469-7

Article  PubMed  PubMed Central  Google Scholar 

Bai Z, Wang Z, Li M et al (2024) Diabetes mellitus and risk of future stroke: evidence from CHARLS and Mendelian randomization analyses. Brain Behav 14:e70151. https://doi.org/10.1002/brb3.70151

Article  CAS  PubMed  PubMed Central  Google Scholar 

Zimmet P, Alberti KGMM, Stern N et al (2019) The circadian syndrome: is the metabolic syndrome and much more. J Intern Med 286:181–191. https://doi.org/10.1111/joim.12924

Article  CAS  PubMed  PubMed Central  Google Scholar 

Shi Z, Tuomilehto J, Kronfeld-Schor N et al (2022) The circadian syndrome is a significant and stronger predictor for cardiovascular disease than the metabolic syndrome—the NHANES survey during 2005–2016. Nutrients 14:5317. https://doi.org/10.3390/nu14245317

Article  PubMed  PubMed Central  Google Scholar 

Fu X, Peng S, Feng XL (2024) Socioeconomic inequalities in depressive symptoms in China: the role of social capital. Heliyon 10:e24918. https://doi.org/10.1016/j.heliyon.2024.e24918

Article  PubMed  PubMed Central  Google Scholar 

Wang J (2024) The longitudinal relationship between leisure activities and depressive symptoms among older Chinese adults: an autoregressive cross-lagged analysis approach. BMC Public Health 24:763. https://doi.org/10.1186/s12889-024-18293-4

Article  PubMed  PubMed Central  Google Scholar 

Patiño-Villada FA, Estrada-Restrepo A, Aristizábal J (2023) Handgrip strength in older adults from Antioquia-Colombia and comparison of cutoff points for dynapenia. Sci Rep 13:1718. https://doi.org/10.1038/s41598-023-28898-1

Article  CAS  PubMed  PubMed Central  Google Scholar 

Yoo MY, Song HJ, Park KH et al (2024) Relationship between eating alone and handgrip strength in Korean older adults. Nutrients 16:654. https://doi.org/10.3390/nu16050654

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kim K, Oh H, Choi YJ et al (2016) Reappraisal of waist circumference cutoff value according to general obesity. Nutr Metab 13:26. https://doi.org/10.1186/s12986-016-0085-y

Article  CAS  Google Scholar 

Nam GE, Park HS (2018) Perspective on diagnostic criteria for obesity and abdominal obesity in Korean adults. J Obes Metab Syndr 27:134–142. https://doi.org/10.7570/jomes.2018.27.3.134

Article  PubMed  PubMed Central  Google Scholar 

Bieniek J, Wilczynski K, Szewieczek J (2016) Fried frailty phenotype assessment components as applied to geriatric inpatients. Clin Interv Aging 11:453–459. https://doi.org/10.2147/CIA.S101369

Article  PubMed  PubMed Central  Google Scholar 

Nguyenhuy M, Chang J, Xu R et al (2022) The Fried frailty phenotype in patients undergoing cardiac surgery: a systematic review and meta-analysis. Heart Surg Forum 25:E652–E659. https://doi.org/10.1532/hsf.4873

Article  PubMed  Google Scholar 

Pamoukdjian F, Laurent M, Martinez-Tapia C et al (2020) Frailty parameters, morbidity and mortality in older adults with cancer: a structural equation modelling approach based on the Fried phenotype. J Clin Med 9:1826. https://doi.org/10.3390/jcm9061826

Article  PubMed  PubMed Central  Google Scholar 

An JN, Kim J, Lee H et al (2022) Serum cystatin C to creatinine ratio is associated with sarcopenia in non-dialysis-dependent chronic kidney disease. Kidney Res Clin Pract 41:580–590. https://doi.org/10.23876/j.krcp.21.214

Article  PubMed  Google Scholar 

Kong X, Liao S, Li Y et al (2024) Correlation between triglyceride glucose index and atherosclerosis. Chin J Clin Res 37:11. https://doi.org/10.13429/j.cnki.cjcr.2024.07.007

Article  CAS  Google Scholar 

Song S, Son D, Baik S et al (2022) Triglyceride glucose-waist circumference (TyG-WC) is a reliable marker to predict non-alcoholic fatty liver disease. Biomedicines 10:2251. https://doi.org/10.3390/biomedicines10092251

Article  CAS  PubMed  PubMed Central  Google Scholar 

Khamseh ME, Malek M, Abbasi R et al (2021) Triglyceride glucose index and related parameters (triglyceride glucose-body mass index and triglyceride glucose-waist circumference) identify nonalcoholic fatty liver and liver fibrosis in individuals with overweight/obesity. Metab Syndr Relat Disord 19:167–173. https://doi.org/10.1089/met.2020.0109

Article  CAS  PubMed