Skip to main content

Advertisement

SpringerLink
Log in

Metabolic syndrome predicts incident disability and functional decline among Chinese older adults: results from the China Health and Retirement Longitudinal Study

  • Original Article
  • Published:
Aging Clinical and Experimental Research Aims and scope Submit manuscript

Abstract

Aims

To investigate the longitudinal association of metabolic syndrome (MetS) and its components with disability outcomes.

Methods

A total of 5875 participants aged 60 and above completed the 2011 and 2015 waves of the China Health and Retirement Longitudinal Study (CHARLS). MetS at baseline was measured by the National Cholesterol Education Program Adult Treatment Panel III criteria. Logistic regressions were conducted to analyze the associations between baseline MetS and incident disability, measured as the onset of limitations regarding instrumental activities of daily living (IADL) and activities of daily living (ADL) 4 years later. Linear regression was adopted to analyze the longitudinal impact of baseline MetS on the number of IADL and ADL limitations in 2015. A comprehensive list of baseline covariates was adjusted in all regression analyses.

Results

Baseline MetS was related to increased odds of incident IADL disability (OR = 1.28, 95% CI 1.05–1.55) and incident ADL disability (OR = 1.27, 95% CI 1.05–1.53) among disability-free participants at baseline. Baseline MetS was also associated with an increase in the number of IADL (beta = 0.15, 95% CI 0.07–0.23) and ADL limitations (beta = 0.10, 95% CI 0.01–0.18), while adjusting for baseline functional performance. Significant MetS component predictors of disability outcomes include abdominal obesity, high blood pressure, and a low level of high-density lipoprotein cholesterol.

Conclusions

Our findings suggest an increased risk of incident disability and deteriorated functional performance over 4 years, associated with the presence of MetS and its components.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Eckel RH, Grundy SM, Zimmet PZ (2005) The metabolic syndrome. Lancet 365:1415–1428. https://doi.org/10.1016/S0140-6736(05)66378-7

    Article  CAS  PubMed  Google Scholar 

  2. Carriere I, Pérès K, Ancelin ML et al (2014) Metabolic syndrome and disability: findings from the prospective three-city study. J Gerontol 69:79–86. https://doi.org/10.1093/gerona/glt101

    Article  CAS  Google Scholar 

  3. Li X, Li X, Fang F et al (2017) Is metabolic syndrome associated with the risk of recurrent stroke: a meta-analysis of cohort studies. J Stroke Cerebrovasc Dis 26:2700–2705. https://doi.org/10.1016/j.jstrokecerebrovasdis.2017.03.014

    Article  PubMed  Google Scholar 

  4. Foong HF, Hamid TA, Ibrahim R et al (2017) Chronic condition as a mediator between metabolic syndrome and cognition among community-dwelling older adults: the moderating role of sex. Geriatr Gerontol Int 17:1914–1920. https://doi.org/10.1111/ggi.12993

    Article  PubMed  Google Scholar 

  5. Penninx BWJH, Nicklas BJ, Study ftHA (2009) Metabolic syndrome and physical decline in older persons: results from the health, aging and body composition study. J Gerontol 64A:96–102. https://doi.org/10.1093/gerona/gln005

    Article  Google Scholar 

  6. Mukamal KJ, Siscovick DS, de Boer IH et al (2018) Metabolic clusters and outcomes in older adults: the cardiovascular health study. J Am Geriatr Soc 66:289–296. https://doi.org/10.1111/jgs.15205

    Article  PubMed  PubMed Central  Google Scholar 

  7. Laudisio A, Bandinelli S, Gemma A et al (2014) Metabolic syndrome and functional ability in older age: the InCHIANTI study. Clin Nutr 33:626–633. https://doi.org/10.1016/j.clnu.2013.08.005

    Article  PubMed  Google Scholar 

  8. Viscogliosi G, Donfrancesco C, Palmieri L et al (2017) The metabolic syndrome and 10-year cognitive and functional decline in very old men. A population-based study. Arch Gerontol Geriatr 70:62–66. https://doi.org/10.1016/j.archger.2016.12.008

    Article  PubMed  Google Scholar 

  9. Blaum CS, West NA, Haan MN (2007) Is the metabolic syndrome, with or without diabetes, associated with progressive disability in older Mexican Americans? J Gerontol 62:766–773. https://doi.org/10.1093/gerona/62.7.766

    Article  Google Scholar 

  10. Blazer DG, Hybels CF, Fillenbaum GG (2006) Metabolic syndrome predicts mobility decline in a community-based sample of older adults. J Am Geriatr Soc 54:502–506. https://doi.org/10.1111/j.1532-5415.2005.00607.x

    Article  PubMed  Google Scholar 

  11. Mazloomzadeh S, Karami Zarandi F, Shoghli A et al (2019) Metabolic syndrome, its components and mortality: a population-based study. Med J Islam Repub Iran 33:11. https://doi.org/10.34171/mjiri.33.11

    Article  PubMed  PubMed Central  Google Scholar 

  12. Mohan V, Deepa M (2006) The metabolic syndrome in developing countries. Diabetes Voice 51 (Special Issue)

  13. Yang M, Xu H, Yang L et al (2018) Metabolic syndrome and disability in Chinese nonagenarians and centenarians. Aging Clin Exp Res 30:943–949. https://doi.org/10.1007/s40520-017-0877-6

    Article  PubMed  Google Scholar 

  14. Mao G, Lu F, Fan X et al. (2020) China’s ageing population: the present situation and prospects. In: Poot J, Roskruge M (eds) Population change and impacts in Asia and the Pacific. New frontiers in regional science: Asian perspectives. Springer Singapore, Singapore, 269–287 https://doi.org/10.1007/978-981-10-0230-4_12

  15. Lu J, Wang L, Li M et al (2017) Metabolic syndrome among adults in China: the 2010 China noncommunicable disease surveillance. J Clin Endocrinol Metab 102:507–515. https://doi.org/10.1210/jc.2016-2477

    Article  PubMed  Google Scholar 

  16. Zhao Y, Hu Y, Smith JP et al (2014) Cohort profile: the China health and retirement longitudinal study (CHARLS). Int J Epidemiol 43:61–68. https://doi.org/10.1093/ije/dys203

    Article  PubMed  Google Scholar 

  17. Stone NJ, Bilek S, Rosenbaum S (2005) Recent national cholesterol education program adult treatment panel III update: adjustments and options. Am J Cardiol 96:53E-59E. https://doi.org/10.1016/j.amjcard.2005.06.006

    Article  PubMed  Google Scholar 

  18. Alberti KG, Zimmet P, Shaw J (2006) Metabolic syndrome—a new world-wide definition. A consensus statement from the international diabetes federation. Diabet Med 23:469–480. https://doi.org/10.1111/j.1464-5491.2006.01858.x

    Article  CAS  PubMed  Google Scholar 

  19. Chen X, Crimmins E, Hu PP et al (2019) Venous blood-based biomarkers in the China health and retirement longitudinal study: rationale, design, and results from the 2015 wave. Am J Epidemiol 188:1871–1877. https://doi.org/10.1093/aje/kwz170

    Article  PubMed  PubMed Central  Google Scholar 

  20. Lei X, Sun X, Strauss J et al (2014) Depressive symptoms and SES among the mid-aged and elderly in China: evidence from the China health and retirement longitudinal study national baseline. Soc Sci Med 120:224–232. https://doi.org/10.1016/j.socscimed.2014.09.028

    Article  PubMed  PubMed Central  Google Scholar 

  21. Blaum CS, West NA, Haan MN (2007) Is the metabolic syndrome, with or without diabetes, associated with progressive disability in older Mexican Americans? J Gerontol A Biol Sci Med Sci 62:766–773. https://doi.org/10.1093/gerona/62.7.766

    Article  PubMed  Google Scholar 

  22. Garcia-Hermoso A, Ramirez-Velez R, Ramirez-Campillo R et al (2017) Relationship between ideal cardiovascular health and disability in older adults: the Chilean National Health Survey (2009–10). J Am Geriatr Soc 65:2727–2732. https://doi.org/10.1111/jgs.15139

    Article  PubMed  Google Scholar 

  23. Krebs M, Roden M (2005) Molecular mechanisms of lipid-induced insulin resistance in muscle, liver and vasculature. Diabetes Obes Metab 7:621–632. https://doi.org/10.1111/j.1463-1326.2004.00439.x

    Article  CAS  PubMed  Google Scholar 

  24. Schaap LA, Pluijm SM, Deeg DJ et al (2006) Inflammatory markers and loss of muscle mass (sarcopenia) and strength. Am J Med 119:526.e9–526.e17. https://doi.org/10.1016/j.amjmed.2005.10.049

    Article  CAS  Google Scholar 

  25. Courties A, Sellam J, Berenbaum F (2017) Metabolic syndrome-associated osteoarthritis. Curr Opin Rheumatol 29:214–222. https://doi.org/10.1097/BOR.0000000000000373

    Article  CAS  PubMed  Google Scholar 

  26. Pérez-Tasigchana RF, León-Muñoz LM, Lopez-Garcia E et al (2017) Metabolic syndrome and insulin resistance are associated with frailty in older adults: a prospective cohort study. Age Ageing 46:807–812. https://doi.org/10.1093/ageing/afx023

    Article  PubMed  Google Scholar 

  27. Liu HX, Ding G, Yu WJ et al (2019) Association between frailty and incident risk of disability in community-dwelling elder people: evidence from a meta-analysis. Public Health 175:90–100. https://doi.org/10.1016/j.puhe.2019.06.010

    Article  CAS  PubMed  Google Scholar 

  28. Visser M, Goodpaster BH, Kritchevsky SB et al (2005) Muscle mass, muscle strength, and muscle fat infiltration as predictors of incident mobility limitations in well-functioning older persons. J Gerontol A Biol Sci Med Sci 60:324–333. https://doi.org/10.1093/gerona/60.3.324

    Article  PubMed  Google Scholar 

  29. Veronese N, Cereda E, Maggi S et al (2016) Osteoarthritis and mortality: a prospective cohort study and systematic review with meta-analysis. Semin Arthritis Rheum 46:160–167. https://doi.org/10.1016/j.semarthrit.2016.04.002

    Article  PubMed  Google Scholar 

  30. Zuliani G, Romagnoni F, Bollini C et al (1999) Low levels of high-density lipoprotein cholesterol are a marker of disability in the elderly. Gerontology 45:317–322. https://doi.org/10.1159/000022112

    Article  CAS  PubMed  Google Scholar 

  31. Assari S, Lankarani RM, Lankarani MM (2014) Cross-country differences in the association between diabetes and disability. J Diabetes Metabol Disord 13:3. https://doi.org/10.1186/2251-6581-13-3

    Article  Google Scholar 

Download references

Funding

We thank the grant support from the National Natural Science Foundation of China (Grant Number 71704006) and the Beijing Social Science Fund (Grant Number 16SRB006). The funding agencies had no direct role in the conduct of the study; the collection, management, analyses, or interpretation of the data; or preparation or approval of the manuscript.

Author information

Authors and Affiliations

  1. National School of Development, Peking University, No. 5 Yiheyuan Road, Haidian, Beijing, 100871, China

    Quan Zhang

  2. School of Social Work, The University of Iowa, 225B North Hall, Iowa, IA, 52242, USA

    Yi Wang

  3. Department of Endocrinology, Peking University First Hospital, No. 8 Xishiku Street, Beijing, 100034, China

    Nan Yu

  4. Institute of Social Science Survey, Peking University, No.5 Yiheyuan Road, Haidian, Beijing, 100871, China

    Hua Ding

  5. Department of Sociology, Central South University, No. 932 Lushannan Road, Changsha, 410083, China

    Danyu Li

  6. School of Health Humanities, Peking University, No. 38 Xueyuan Road, Beijing, 100191, China

    Xinyi Zhao

Authors
  1. Quan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yi Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nan Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hua Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Danyu Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xinyi Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xinyi Zhao.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Ethical approval

The protocols of CHARLS were approved by the Ethical Committee at Peking University. All participants in CHARLS gave informed consent.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 34 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Q., Wang, Y., Yu, N. et al. Metabolic syndrome predicts incident disability and functional decline among Chinese older adults: results from the China Health and Retirement Longitudinal Study. Aging Clin Exp Res 33, 3073–3080 (2021). https://doi.org/10.1007/s40520-021-01827-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40520-021-01827-w

Keywords

Search

Navigation