Frailty and Risk of Fractures in Patients With Type 2 Diabetes
Jerilynn C Prior, William D Leslie, Lehana Thabane
S M Kaiser, Christopher S Kovacs, Tassos Anastassiades, Tanveer Towheed, Kelly Davison, Mitchell Levine, David Goltzman, Jonathan D Adachi, Alexandra Papaioannou, Guowei Li, K Shawn Davison, Robert G Josse, Stephanie M Kaiser, CaMos Research Group
We aimed to explore whether frailty was associated with fracture risk and whether frailty could modify the propensity of type 2 diabetes toward increased risk of fractures.Research design and methodsData were from a prospective cohort study. Our primary outcome was time to the first incident clinical fragility fracture; secondary outcomes included time to hip fracture and to clinical spine fracture. Frailty status was measured by a Frailty Index (FI) of deficit accumulation. The Cox model incorporating an interaction term (frailty × diabetes) was used for analyses.
Results
The analysis included 3,149 (70% women) participants; 138 (60% women) had diabetes. Higher bone mineral density and FI were observed in participants with diabetes compared with control subjects. A significant relationship between the FI and the risk of incident fragility fractures was found, with a hazard ratio (HR) of 1.02 (95% CI 1.01-1.03) and 1.19 (95% CI 1.10-1.33) for per-0.01 and per-0.10 FI increase, respectively. The interaction was also statistically significant (P = 0.018). The HR for per-0.1 increase in the FI was 1.33 for participants with diabetes and 1.19 for those without diabetes if combining the estimate for the FI itself with the estimate from the interaction term. No evidence of interaction between frailty and diabetes was found for risk of hip and clinical spine fractures.
Conclusions
Participants with type 2 diabetes were significantly frailer than individuals without diabetes. Frailty increases the risk of fragility fracture and enhances the effect of diabetes on fragility fractures. Particular attention should be paid to diabetes as a risk factor for fragility fractures in those who are frail.
frailty index type 2 diabetes fracture risk, diabetes frailty fragility fracture interaction Cox model, Prior JC diabetes bone mineral density fracture paradox, frailty deficit accumulation osteoporosis diabetes prospective cohort, type 2 diabetes higher BMD increased fracture risk frailty, Canadian Multicentre Osteoporosis Study diabetes frailty fractures, frailty modifies diabetes fracture risk older adults, Li Adachi frailty diabetes fracture hazard ratio, bone mineral density paradox type 2 diabetes fragility fracture, geriatric frailty assessment osteoporotic fracture prediction diabetes
PMID 30692240 30692240 DOI 10.2337/dc18-1965 10.2337/dc18-1965
Cite this article
Li, G., Prior, J. C., Leslie, W. D., Thabane, L., Papaioannou, A., Josse, R. G., Kaiser, S. M., Kovacs, C. S., Anastassiades, T., Towheed, T., Davison, K. S., Levine, M., Goltzman, D., Adachi, J. D., & CaMos Research Group (2019). Frailty and Risk of Fractures in Patients With Type 2 Diabetes. Diabetes care, 42(4), 507-513. https://doi.org/10.2337/dc18-1965
Li G, Prior JC, Leslie WD, Thabane L, Papaioannou A, Josse RG, et al. Frailty and Risk of Fractures in Patients With Type 2 Diabetes. Diabetes Care. 2019;42(4):507-513. doi:10.2337/dc18-1965
Li, G., et al. "Frailty and Risk of Fractures in Patients With Type 2 Diabetes." Diabetes care, vol. 42, no. 4, 2019, pp. 507-513.
We aimed to assess whether individuals with type 2 diabetes (T2D) have increased risk of vertebral fractures (VFs) and to estimate nonvertebral fracture and mortality risk among individuals with both prevalent T2D and VFs. Methods: A systematic PubMed search was performed to identify studies that investigated the relationship between T2D and VFs. Cohorts providing individual participant data (IPD) were also included. Estimates from published summary data and IPD cohorts were pooled in a random-effects meta-analysis. Multivariate Cox regression models were used to estimate nonvertebral fracture and mortality risk among individuals with T2D and VFs. Across 15 studies comprising 852,705 men and women, individuals with T2D had lower risk of prevalent (odds ratio [OR] 0.84 [95% CI 0.74-0.95]; I (2) = 0.0%; P (het) = 0.54) but increased risk of incident VFs (OR 1.35 [95% CI 1.27-1.44]; I (2) = 0.6%; P (het) = 0.43). In the IPD cohorts (N = 19,820), risk of nonvertebral fractures was higher in those with both T2D and VFs compared with those without T2D or VFs (hazard ratio [HR] 2.42 [95% CI 1.86-3.15]) or with VFs (HR 1.73 [95% CI 1.32-2.27]) or T2D (HR 1.94 [95% CI 1.46-2.59]) alone. Individuals with both T2D and VFs had increased mortality compared with individuals without T2D and VFs (HR 2.11 [95% CI 1.72-2.59]) or with VFs alone (HR 1.84 [95% CI 1.49-2.28]) and borderline increased compared with individuals with T2D alone (HR 1.23 [95% CI 0.99-1.52]). Based on our findings, individuals with T2D should be systematically assessed for presence of VFs, and, as in individuals without T2D, their presence constitutes an indication to start osteoporosis treatment for the prevention of future fractures.
AndrologyTestosterone and MetabolismHormonal AssessmentSHBG and Insulin Resistance
Previous reports of an association between low testosterone levels and diabetes risk were often confounded by covariation of sex hormone-binding globulin (SHBG) and testosterone measurements. Measurements of bioavailable and free testosterone, more reliable indexes of biologically active testosterone, were examined for their associations with markers of insulin resistance and body fat measures in 221 middle-aged nondiabetic men. Methods: Bioavailable and free testosterone were calculated from the concentrations of total testosterone, SHBG, and albumin, and they were not significantly correlated with SHBG (r = 0.07-0.1). In contrast, total testosterone correlated significantly with SHBG (r = 0.63). We evaluated the relationship between these measures of circulating testosterone and markers for insulin resistance (i.e., fasting insulin, C-peptide, and homeostasis model assessment for insulin resistance [HOMA-IR]) as well as total body fat (assessed by dual-energy X-ray absorptiometry [DEXA]) and abdominal fat distribution (assessed by single-slice computed tomography [CT]). Bioavailable, free, and total testosterone and SHBG all correlated significantly with fasting insulin (age-adjusted r = -0.15 [P = 0.03], -0.14 [P = 0.03], -0.32 [P < 0.0001], and -0.38 [P < 0.0001], respectively), fasting C-peptide (r = -0.18 [P = 0.009] to -0.41 [P < 0.0001]), HOMA-IR (r = -0.15 [P = 0.03] to - 0.39 [P < 0.0001]), and body fat measures (r = -0.17 [P = 0.008] to -0.44 [P < 0.0001]). Only SHBG and total testosterone were significantly associated with fasting glucose (r = -0.20 [P = 0.003] to -0.21 [P = 0.002]). In multivariate analysis, bioavailable or free testosterone was significantly and inversely associated with insulin, C-peptide, and HOMA-IR, but this was not independent of total body or abdominal fat. SHBG was a significant determinant of insulin, C-peptide, and HOMA-IR, independent of body fat. The associations between total testosterone and insulin resistance were confounded by SHBG. The inverse association between testosterone and insulin resistance, independent of SHBG, was mediated through body fat.
Twenty-eight patients with type I diabetes mellitus, legally blind as a result of proliferative retinopathy, were recruited into a program designed to teach and evaluate tactile methods for self-monitoring of blood glucose (SMBG). Vision ranged from "blind" to "able to read large print." Techniques with wipe-off strips (Chemstrip bG or BM Test BG, Boehringer-Mannheim, Canada Ltd., Dorval, Quebec, Canada) use the opposite hand as a guide, operation of timing devices by touch, and special methods for labeling and storing strips. Methods with wash-off strips (Dextrostix, Ames Division, Miles Laboratories, Rexdale, Ontario, Canada) employ the fingers as a guide in directing the wash water. The accuracy of tactile methods was documented. Clinical parameters of glucose control improved in patients with adequate data after 6 mo of tactile SMBG. Glycosylated hemoglobin in 17 patients decreased from 11.3 +/- 2.1% to 9.4 +/- 1.5% (P = 0.005). Patients experienced significantly fewer reactions and low blood sugar readings as well as lowering of mean blood glucose values from 158 +/- 56 to 141 +/- 51 (P = 0.025).