U-shaped link of health checkup data and need for care using a time-dependent cox regression model with a restricted cubic spline.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
22 05 2023
22 05 2023
Historique:
received:
09
11
2022
accepted:
20
04
2023
medline:
24
5
2023
pubmed:
23
5
2023
entrez:
22
5
2023
Statut:
epublish
Résumé
We explored risk indicators likely to result in older adults needing certified long-term care in Japan and ascertained whether this relationship forms a U-shaped link. We analyzed a community-based cohort of residents in Kitanagoya City, Aichi Prefecture, Japan. Participants were 3718 individuals aged 65 years and above who underwent health examinations between April 1, 2011 and March 31, 2012. For continuous clinical variables, we applied a time-dependent Cox regression model. Two types of models were applied-a linear and nonlinear model with restricted cubic splines-to assess the U-shaped association. Statistical significance (set at 0.05) for the nonlinearity was tested by comparing the spline and linear models. Among the participants, 701 were certified as needing Level 1 care or higher during a follow-up. Among the continuous clinical variables, the nonlinear model for body mass index, systolic blood pressure, high-density lipoprotein cholesterol, alanine aminotransferase, aspartate aminotransferase, and γ-glutamyl transpeptidase revealed significant U-shaped associations as compared with the linear model in which the outcome was a certification of the need for nursing care. These results provide an important insight into the usefulness of nonlinear models for predicting the risk of such certification.
Identifiants
pubmed: 37217488
doi: 10.1038/s41598-023-33865-x
pii: 10.1038/s41598-023-33865-x
pmc: PMC10203122
doi:
Substances chimiques
Cholesterol, HDL
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
7537Informations de copyright
© 2023. The Author(s).
Références
Epidemiology. 1995 Jul;6(4):450-4
pubmed: 7548361
Obesity (Silver Spring). 2016 Oct;24(10):2240-7
pubmed: 27589069
Int J Environ Res Public Health. 2022 Feb 14;19(4):
pubmed: 35206350
Liver Int. 2014 Feb;34(2):296-304
pubmed: 24219360
Geriatr Gerontol Int. 2015 Jun;15(6):673-87
pubmed: 25656311
J Rural Med. 2017 Nov;12(2):68-84
pubmed: 29255523
Hypertension. 2022 Jan;79(1):218-229
pubmed: 34775786
Annu Rev Public Health. 1999;20:145-57
pubmed: 10352854
Eur Heart J. 2017 Aug 21;38(32):2459-2472
pubmed: 28444290
BMC Med Res Methodol. 2012 Feb 29;12:21
pubmed: 22375553
Lancet. 2009 Mar 28;373(9669):1083-96
pubmed: 19299006
Lancet Diabetes Endocrinol. 2015 Jun;3(6):431-436
pubmed: 25866264
Theor Med Bioeth. 1998 Dec;19(6):591-607
pubmed: 10051792
Nat Rev Endocrinol. 2018 Oct;14(10):591-604
pubmed: 30022099
Sci Rep. 2018 Feb 28;8(1):3764
pubmed: 29491346
BMJ. 2016 May 04;353:i2156
pubmed: 27146380
Clin Exp Med. 2022 Feb;22(1):75-81
pubmed: 34240258
J Alzheimers Dis. 2021;79(4):1775-1784
pubmed: 33459646
Nihon Koshu Eisei Zasshi. 2017;64(5):246-257
pubmed: 28626152
Epidemiology. 1995 Jul;6(4):356-65
pubmed: 7548341
Lancet. 2016 Aug 20;388(10046):776-86
pubmed: 27423262
Nihon Koshu Eisei Zasshi. 2005 Mar;52(3):226-34
pubmed: 15859121
Medicine (Baltimore). 2016 Aug;95(31):e4452
pubmed: 27495075
J Am Geriatr Soc. 2005 Mar;53(3):522-7
pubmed: 15743300
J Clin Epidemiol. 2009 May;62(5):511-7.e1
pubmed: 19135859
N Engl J Med. 2010 Dec 2;363(23):2211-9
pubmed: 21121834
Lancet Diabetes Endocrinol. 2018 Dec;6(12):944-953
pubmed: 30389323
Stat Med. 2006 Jan 15;25(1):127-41
pubmed: 16217841
Geriatr Gerontol Int. 2018 Apr;18(4):521-529
pubmed: 29239071