Cardiovascular risk profile and frailty in Japanese outpatients: the Nambu Cohort Study
- PMID: 32203449
- DOI: 10.1038/s41440-020-0427-z
Cardiovascular risk profile and frailty in Japanese outpatients: the Nambu Cohort Study
Abstract
Epidemiologic findings indicate that unfavorable cardiovascular (CV) risk profiles, such as elevated systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), and overweight, decelerate with aging. Few studies, however, have evaluated the association between the CV risk profile and frailty. We performed a cross-sectional analysis using the baseline data of a prospective cohort study. A total of 599 subjects (age, 78 [range: 70-83] years; men, 50%) were analyzed in an outpatient setting. Frailty was diagnosed in 37% of the patients according to the Kihon Checklist score. An unfavorable CV risk profile was associated with a lower risk of frailty. The adjusted odds ratios (ORs; 95% confidence interval [CI]) of each CV risk factor for frailty were as follows: SBP (each 10 mmHg increase) 0.83 (0.72-0.95), LDL-C (each 10 mg/dl increase) 0.96 (0.86-1.05), and body mass index (each 1 kg/m2 increase) 1.03 (0.97-1.10). Moreover, the total number of CV risk factors within the optimal range was significantly associated with the risk of frailty with the following ORs (95% CI): 1, 2.30 (0.75-8.69); 2, 3.22 (1.07-11.97); and 3, 4.79 (1.56-18.05) compared with patients having no risk factors within optimal levels (p for trend 0.008). Abnormal homeostasis might lead to lower levels of CV risk factors, which together result in "reverse metabolic syndrome." Our findings indicate that a favorable CV risk profile is associated with frailty.
Keywords: Cardiovascular risk; Cohort study; Frailty; Reverse metabolic syndrome.
Similar articles
-
Achievement of low density lipoprotein (LDL) cholesterol targets in primary and secondary prevention: Analysis of a large real practice database in Italy.Atherosclerosis. 2019 Jun;285:40-48. doi: 10.1016/j.atherosclerosis.2019.03.017. Epub 2019 Apr 8. Atherosclerosis. 2019. PMID: 31003091
-
Association of Frailty and Cardiometabolic Risk Among Community-Dwelling Middle-Aged and Older People: Results from the I-Lan Longitudinal Aging Study.Rejuvenation Res. 2015 Dec;18(6):564-72. doi: 10.1089/rej.2015.1699. Epub 2015 Nov 10. Rejuvenation Res. 2015. PMID: 26556635
-
Serum low-density lipoprotein cholesterol level is strong risk factor for acquired color vision impairment in young to middle-aged Japanese men: the Okubo Color Study Report 2.Atherosclerosis. 2010 Jun;210(2):542-7. doi: 10.1016/j.atherosclerosis.2009.11.039. Epub 2009 Dec 1. Atherosclerosis. 2010. PMID: 20031130
-
Validity of the Kihon Checklist for assessing frailty status.Geriatr Gerontol Int. 2016 Jun;16(6):709-15. doi: 10.1111/ggi.12543. Epub 2015 Jul 14. Geriatr Gerontol Int. 2016. PMID: 26171645
-
Phenotypic Frailty Assessment in Mice: Development, Discoveries, and Experimental Considerations.Physiology (Bethesda). 2020 Nov 1;35(6):405-414. doi: 10.1152/physiol.00016.2020. Physiology (Bethesda). 2020. PMID: 33052773 Free PMC article. Review.
Cited by
-
Body mass index and sarcopenia and mortality risk among older hypertensive outpatients; the Nambu Cohort Study.Hypertens Res. 2024 Oct 12. doi: 10.1038/s41440-024-01921-2. Online ahead of print. Hypertens Res. 2024. PMID: 39394516
-
Unraveling the metabolic underpinnings of frailty using multicohort observational and Mendelian randomization analyses.Aging Cell. 2023 Aug;22(8):e13868. doi: 10.1111/acel.13868. Epub 2023 May 15. Aging Cell. 2023. PMID: 37184129 Free PMC article.
-
Baseline Lipoprotein(a) Levels and Long-Term Cardiovascular Outcomes After Acute Myocardial Infarction.J Korean Med Sci. 2023 Apr 3;38(13):e102. doi: 10.3346/jkms.2023.38.e102. J Korean Med Sci. 2023. PMID: 37012687 Free PMC article.
-
Current topics of frailty in association with hypertension and other medical conditions.Hypertens Res. 2023 May;46(5):1188-1194. doi: 10.1038/s41440-023-01200-6. Epub 2023 Feb 15. Hypertens Res. 2023. PMID: 36792774 Free PMC article. Review.
-
Predictors of Metformin Failure: Repurposing Electronic Health Record Data to Identify High-Risk Patients.J Clin Endocrinol Metab. 2023 Jun 16;108(7):1740-1746. doi: 10.1210/clinem/dgac759. J Clin Endocrinol Metab. 2023. PMID: 36617249 Free PMC article.
References
-
- Xue Q-L. The frailty syndrome: definition and natural history. Clin Geriatr Med. 2011;27:1–15. https://doi.org/10.1016/j.cger.2010.08.009 - DOI - PubMed - PMC
-
- Satake S, Shimokata H, Senda K, Kondo I, Toba K. Validity of total Kihon Checklist Score for predicting the incidence of 3-year dependency and mortality in a community-dwelling older population. J Am Med Dir Assoc. 2017;18:552.e1–e6. https://doi.org/10.1016/j.jamda.2017.03.013 - DOI
-
- Yamada Y, Nanri H, Watanabe Y, Yoshida T, Yokoyama K, Itoi A, et al. Prevalence of frailty assessed by fried and Kihon Checklist Indexes in a prospective cohort study: design and demographics of the Kyoto-Kameoka Longitudinal Study. J Am Med Dir Assoc. 2017;18:733.e7–e15. https://doi.org/10.1016/j.jamda.2017.02.022 - DOI
-
- Fried LP, Tangen CM, Walston J, Newman AB, Hirsch C, Gottdiener J, et al. Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci. 2001;56:M146–56. https://doi.org/10.1093/gerona/56.3.M146 - DOI - PubMed
-
- Gale CR, Cooper C, Sayer AA. Prevalence of frailty and disability: findings from the English Longitudinal Study of Ageing. Age Ageing. 2015;44:162–5. https://doi.org/10.1093/ageing/afu148 - DOI - PubMed
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Medical