The Association of Malnutrition and Health-Related Factors among 474,467 Older Community-Dwellers: A Population-Based Data Mining Study in Guangzhou, China.

Publisher: MDPI Publishing Country of Publication: Switzerland NLM ID: 101521595 Publication Model: Electronic Cited Medium: Internet ISSN: 2072-6643 (Electronic) Linking ISSN: 20726643 NLM ISO Abbreviation: Nutrients Subsets: MEDLINE

Original Publication: Basel, Switzerland : MDPI Publishing

Malnutrition*/epidemiology ; Hypertension*/epidemiology ; Data Mining*; Humans ; Aged ; China/epidemiology ; Male ; Female ; Prevalence ; Risk Factors ; Aged, 80 and over ; Independent Living ; Nutritional Status ; Diabetes Mellitus/epidemiology ; Obesity/epidemiology ; Diet ; Exercise ; Logistic Models ; Dyslipidemias/epidemiology

Background: This study aimed to examine the prevalence and associated factors of malnutrition in older community-dwellers and explore the interaction between associated factors.
Methods: A total of 474,467 older community-dwellers aged 65 or above were selected in Guangzhou, China. We used a two-step methodology to detect the associated factors of malnutrition and constructed logistic regression models to explore the influencing factors and interactive effects on three patterns of malnutrition.
Results: The prevalence of malnutrition was 22.28%. Older adults with both hypertension and diabetes (RERI = 0.13), both meat or fish diet and hypertension (RERI = 0.79), and both meat or fish diet and diabetes (RERI = 0.81) had positive additive interaction effects on the risk of obesity, whereas those on a vegetarian diet with hypertension (RERI = -0.25) or diabetes (RERI = -0.19) had negative additive interaction effects. Moreover, the interactions of physical activity with a meat or fish diet (RERI = -0.84) or dyslipidemia (RERI = -0.09) could lower the risk of obesity.
Conclusions: Malnutrition was influenced by different health factors, and there were interactions between these influencing factors. Pertinent dietary instruction should be given according to different nutritional status indexes and the prevalence of metabolic diseases to avoid the occurrences of malnutrition among older adults.

Br J Community Nurs. 2012 Nov;17(11):529-30, 532-4. (PMID: 23124422)
Adv Nutr. 2019 Mar 1;10(2):205-218. (PMID: 30801613)
BMC Public Health. 2013 Jun 12;13:573. (PMID: 23758758)
Curr Opin Clin Nutr Metab Care. 2001 Jul;4(4):295-300. (PMID: 11458024)
Int J Mol Sci. 2023 Mar 22;24(6):. (PMID: 36983057)
BMJ Open. 2022 Mar 9;12(3):e056100. (PMID: 35264361)
BMC Geriatr. 2018 Aug 30;18(1):199. (PMID: 30165826)
Eur J Epidemiol. 2005;20(7):575-9. (PMID: 16119429)
J Nutr Health Aging. 2015 Jan;19(1):26-32. (PMID: 25560813)
Physiol Behav. 2008 May 23;94(2):252-8. (PMID: 18342897)
Biomed Environ Sci. 2021 May 20;34(5):337-347. (PMID: 34059170)
Eur Heart J. 2021 Mar 21;42(12):1136-1143. (PMID: 33313747)
J Gen Intern Med. 2022 Nov;37(14):3545-3553. (PMID: 35088201)
Clin Interv Aging. 2010 Aug 09;5:207-16. (PMID: 20711440)
Nutr Res Pract. 2019 Jun;13(3):222-229. (PMID: 31214290)
BMC Geriatr. 2017 Jul 3;17(1):136. (PMID: 28673255)
Clin Interv Aging. 2021 May 21;16:887-895. (PMID: 34054294)
Zhonghua Liu Xing Bing Xue Za Zhi. 2022 Jun 10;43(6):915-921. (PMID: 35725350)
Age Ageing. 2019 Jan 1;48(1):38-48. (PMID: 30188972)
J Family Community Med. 2015 Jan-Apr;22(1):39-43. (PMID: 25657610)
J Diabetes Complications. 2017 Jul;31(7):1169-1174. (PMID: 28433448)
BMC Res Notes. 2019 Apr 30;12(1):246. (PMID: 31039794)
J Nutr Health Aging. 2017;21(9):943-953. (PMID: 29083434)
BMC Public Health. 2020 May 13;20(1):675. (PMID: 32404080)
J Alzheimers Dis. 2021;83(4):1741-1752. (PMID: 34459393)
Public Health Nutr. 2011 Nov;14(11):1893-9. (PMID: 21426623)
BMC Geriatr. 2016 Jul 16;16:139. (PMID: 27423703)
Nutr Metab Cardiovasc Dis. 2021 Jan 4;31(1):52-59. (PMID: 32988726)
Nutrients. 2017 Jun 14;9(6):. (PMID: 28613258)
Aging Med (Milton). 2022 Oct 03;5(3):191-203. (PMID: 36247340)
Nutrients. 2023 Sep 12;15(18):. (PMID: 37764729)
Mech Ageing Dev. 2014 Mar-Apr;136-137:76-84. (PMID: 24486557)
Nutrients. 2017 Aug 03;9(8):. (PMID: 28771192)
Lancet. 2023 Mar 18;401(10380):951-966. (PMID: 36716756)
BMC Geriatr. 2020 Nov 23;20(1):498. (PMID: 33228557)
Public Health Nutr. 2018 Dec;21(17):3129-3134. (PMID: 30282567)
Environ Health Prev Med. 2015 Mar;20(2):116-22. (PMID: 25511645)
Nurs Stand. 2018 Jun 6;33(3):69-76. (PMID: 29873473)
Cell Physiol Biochem. 2016;38(5):1681-94. (PMID: 27160520)
J Am Med Dir Assoc. 2016 Jan;17(1):17-23. (PMID: 26712488)
PLoS One. 2020 Feb 7;15(2):e0228058. (PMID: 32032376)
Metabolism. 2019 Mar;92:163-169. (PMID: 30385379)
Front Public Health. 2022 Sep 20;10:998769. (PMID: 36203673)
Food Nutr Bull. 2014 Jun;35(2):230-43. (PMID: 25076771)
Nutrients. 2019 Apr 11;11(4):. (PMID: 30979052)
Nutrients. 2023 Sep 02;15(17):. (PMID: 37686866)
Lancet. 2020 Jan 4;395(10217):65-74. (PMID: 31852602)
Semin Nephrol. 2006 Jul;26(4):275-82. (PMID: 16949465)

72104061 National Natural Science Foundation of China; 202201010022 Science and Technology Plan Project of Guangzhou [202201010022] and Safe Kids Worldwide-China; No.2021-2023-12 The Key Project of Medicine Discipline of Guangzhou; No.202102100001 Basic Research Project of Key Laboratory of Guangzhou; SL2022A03J01446 Basic and Applied Research Project of Guangzhou

Keywords: data mining; health-related factors; older community-dwellers; patterns of malnutrition; prevalence

Date Created: 20240511 Date Completed: 20240511 Latest Revision: 20240513

20240513

PMC11085532

10.3390/nu16091338

38732585