Obesity paradox on the survival of elderly patients with diabetes: an AHAP-based study
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Background and objectives
Overweight and obesity are among the important challenges in health issues and survival of elderly people. The current study aimed to evaluate the survival rate of elderly patients with diabetes, and its influencing factors, on the basis of body mass index (BMI).
Methods and materials
The design of the current study was based on the Amirkola Health and Aging Project (AHAP) cohort. The 5–year survival rate of elderly people with diabetes and the factors that influence the mortality rate by Cox regression model were analyzed.
Out of 1616 elderly people who were evaluated in the current study, 501 (31%) had diabetes. The results showed that diabetes significantly increased the mortality rate (adjusted hazard ratio [HR] = 2.10; 95% confidence interval [CI]: 1.57–2.81; P < 0.001). Furthermore, overweight (HR = 0.41; 95%CI: 0.24–0.75; P = 0.002), obesity (HR = 0.30; 95% CI: 0.41–0.63; P = 0.002), history of diabetes (HR = 0.56; 95%CI: 0.34–0.93; P = 0.024), moderate and high physical activity level (HR = 0.36; 95%CI: 0.13–0.99; P = 0.049) decreased the risk of mortality and central obesity (HR = 1.76; 95% CI: 1.01–3.11; P = 0.049), fasting blood sugar ≥200 (HR = 2.46; 95% CI: 1.46–4.15; P < 0.001), brain stroke, and neurological diseases (HR = 3.12; 95% CI: 1.78–5.49; P < 0.001) increased the risk of mortality.
Although overweight and obesity significantly improved the risk of mortality in elderly patients with diabetes, central obesity is still considered as an important risk factor.
KeywordsObesity Survival Diabetes mellitus Aging
amirkola health and ageing project
body mass index
cox proportional hazard
duke social support index
fasting blood sugar
geriatric depression scale
international diabetes federation
physical activity scale for elderly
The authors would like to thank all authorities of Babol University of Medical Sciences,
AHAP collaboration and the elderly participants of this project.
AB, SRH, RC and RG conceived and designed the study. AB, MY, RR and AS gathered the data. AB performed the statistical analysis. AB drafted the manuscript. SRH and RG critically revised the manuscript. All authors read and approved the final manuscript.
Compliance with ethical standards
The authors declare that they have no competing interests.
Ethics approval and consent to participate
Our study was reviewed and approved by ethics committee, Babol University of Medical Sciences.
- 1.Rahelić D. 7th edition of IDF diabetes atlas-call for immediate action. Lijec Vjesn. 2016;138(1–2):57–8. https://www.ncbi.nlm.nih.gov/pubmed/?term=27290816.PubMedGoogle Scholar
- 2.Nasli-Esfahani E, Farzadfar F, Kouhnavard M, Ghodssi-Ghassemabadi R, Khajavi A, Peimani M, et al. Iran diabetes research roadmap (IDRR) study: a preliminary study on diabetes research in the world and Iran. J Diabetes Metab Disord. 2017;16(9) https://doi.org/10.1186/s40200-017-0291-9. https://www.ncbi.nlm.nih.gov/pubmed/?term=28239599.
- 7.Hajian-Tilaki KO, Heidari B. Prevalence of obesity, central obesity and the associated factors in urban population aged 20-70 years, in the north of Iran: a population-based study and regression approach. Obes Rev. 2007;8(1):3–10. https://www.ncbi.nlm.nih.gov/pubmed/17212790.CrossRefPubMedGoogle Scholar
- 8.Noroozian M. The elderly population in Iran: an ever growing concern in the health system. Iran J Psychiatry Behav Sci. 2012;6(2):1–6. https://www.ncbi.nlm.nih.gov/pubmed/?term=24644476.PubMedPubMedCentralGoogle Scholar
- 11.Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 2013; 36 (Suppl 1): S67-S74. https://doi.org/10.2337/dc13-S067, Diagnosis and Classification of Diabetes Mellitus.
- 13.Zghebi SS, Steinke DT, Carr MJ, Rutter MK, Emsley RA, Ashcroft DM. Examining trends in type 2 diabetes incidence, prevalence and mortality in the UK between 2004 and 2014. Diabetes Obes Metab. 2017;19:1537–45. https://doi.org/10.1111/dom.12964. https://www.ncbi.nlm.nih.gov/pubmed/28387052.CrossRefPubMedGoogle Scholar
- 16.Dhana K, Kavousi M, Ikram MA, Tiemeier HW, Hofman A1, Franco OH. Body shape index in comparison with other anthropometric measures in prediction of total and cause-specific mortality. J Epidemiol Community Health 2016; 70(1):90–96. https://www.ncbi.nlm.nih.gov/pubmed/26160362.
- 20.Bouchard DR, Janssen I. Dynapenic-obesity and Physical function in older adults. J Gerontol A Biol Sci Med Sci 2010; 65(1):71–77. https://www.ncbi.nlm.nih.gov/pubmed/19887536.
- 23.Murphy RA, Reinders I, Garcia ME, Eiriksdottir G, Launer LJ, Benediktsson R, Gudnason V, Jonsson PV, Harris TB, Age, Gene/Environment Susceptibility-Reykjavik Study (AGES-Reykjavik). Age, gene/environment susceptibility-Reykjavik study (AGES-Reykjavik). Adipose tissue, muscle, and function: potential mediators of associations between body weight and mortality in older adults with type 2 diabetes. Diabetes Care 2014; 37(12): 3213–3219. https://www.ncbi.nlm.nih.gov/pubmed/?term=25315206.
- 24.Srikanthan P, Karlamangla AS. Relative muscle mass is inversely associated with insulin resistance and prediabetes. Findings from the third National Health and nutrition examination survey. Format: Abstract J Clin Endocrinol Metab. 2011;96(9):2898–903. https://www.ncbi.nlm.nih.gov/pubmed/?term=21778224.Google Scholar
- 26.Cho MR, Park JK, Choi WJ, Cho AR, Lee YJ. Serum ferritin level is positively associated with insulin resistance and metabolic syndrome in postmenopausal women: a nationwide population-based study. Maturitas. 2017;103:3–7. https://doi.org/10.1016/j.maturitas.2017.06.004. https://www.ncbi.nlm.nih.gov/pubmed/28778329.CrossRefPubMedGoogle Scholar
- 27.Morimoto A, Tatsumi Y, Deura K, Mizuno S, Ohno Y, Watanabe S. Impact of cigarette smoking on impaired insulin secretion and insulin resistance in Japanese men: the Saku study. Journal of Diabetes Investigation. 2013;4(3):274–80. https://www.ncbi.nlm.nih.gov/pubmed/24843666.CrossRefPubMedGoogle Scholar
- 28.Emerging Risk Factors Collaboration, Sarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, et al. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet 2010; 375(9733): 2215–2222 https://www.ncbi.nlm.nih.gov/pubmed/?term=20609967.
- 29.Lieber BA, Taylor B, Appelboom G, Prasad K, Bruce S, Yang A, et al. Meta-analysis of telemonitoring to improve HbA1c levels: promise for stroke survivors. J Clin Neurosci. 2015;22(5):807–11. https://www.ncbi.nlm.nih.gov/pubmed/?term=25791996.CrossRefPubMedGoogle Scholar
- 30.Bijani A, Esmaili H, Ghadimi R, Babazadeh A, Rezaei R, Cumming RG, et al. Development and validation of a semi-quantitative food frequency questionnaire among older people in north of Iran. Caspian J Intern Med. 2018;9(1):78–86. http://caspjim.com/article-1-1241-en.html.PubMedPubMedCentralGoogle Scholar