OBJECTIVE

There is growing evidence that weight loss is associated with increased fracture risk in the general population. As patients with diabetes often lose weight intentionally or unintentionally, we aimed to investigate prospectively the relationship between weight loss from maximum body weight and fracture risk.

RESEARCH DESIGN AND METHODS

A total of 4,706 Japanese participants with type 2 diabetes (mean age 66 years), including 2,755 men and 1,951 postmenopausal women, were followed for a median of 5.3 years and were divided according to weight loss from maximum weight: <10%, 10% to <20%, 20% to <30%, and ≥30%. The primary outcomes were fragility fractures defined as fractures at sites of hip and spine.

RESULTS

During the follow-up period, fragility fractures occurred in 198 participants. The age- and sex-adjusted incidence rates per 1,000 person-years in all participants were 6.4 (<10% weight loss from maximum body weight), 7.8 (10% to <20%), 11.7 (20% to <30%), and 19.2 (≥30%) (P for trend <0.001). Multivariate-adjusted hazard ratios for fragility fractures compared with reference (<10% weight loss) were 1.48 (95% CI 0.79–2.77) in the 10% to <20% group, 2.23 (1.08–4.64) in 20% to <30%, and 5.20 (2.15–12.57) in ≥30% in men, and 1.19 (0.78–1.82) in 10% to <20%, 1.62 (0.96–2.73) in 20% to <30%, and 1.97 (0.84–4.62) in ≥30% in postmenopausal women.

CONCLUSIONS

The current study demonstrates that ≥20% body weight loss from maximum weight is a significant risk factor for fragility fractures in patients with type 2 diabetes, especially in men.

Epidemiological studies have shown an increased bone fracture risk in patients with type 2 diabetes despite a normal to high bone mineral density (BMD) compared with individuals without diabetes (1,2). Because excess mortality is well described in patients with hip or spine fractures (3,4), an understanding of the association between diabetes and fragility fractures may be needed to prolong life expectancy of patients with diabetes. The proposed mechanism of the association is multifactorial, including nonenzymatic glycation of collagen, decreased bone turnover, oxidative stress microvascular disease, certain diabetes medications, and an increased risk of falling (2,5), although the mechanism is not yet fully understood.

In terms of body weight (BW) change in patients with type 2 diabetes, there is a tendency toward BW loss after diabetes diagnosis (6,7), which may be a result of treatment for obesity or of the natural course of diabetes with progressive insulin deficiency. In the general population, there is growing evidence that BW loss is significantly associated with an increased fracture risk (813). Recently, studies have reported that intentional BW loss decreases BMD in patients with type 2 diabetes (14,15). Furthermore, fracture risk may increase with new BW-lowering therapeutics for patients with type 2 diabetes, such as sodium–glucose cotransporter 2 inhibitors (16,17), glucagon-like peptide 1 receptor agonists (18), and bariatric surgery (19). However, there are few large-scale epidemiological studies examining the relationship between BW loss and incident fracture risk in patients with diabetes. In this context, we aimed to investigate prospectively the relationship between BW loss and fracture risk in Japanese patients with type 2 diabetes.

Study Participants

The Fukuoka Diabetes Registry is a multicenter prospective study (clinical trial reg. no. UMIN 000002627, www.umin.ac.jp/ctr/) designed to investigate the influence of modern treatments on the prognoses of patients with diabetes. The registry includes patients who regularly attended teaching hospitals certified by the Japan Diabetes Society or certified diabetes clinics in Fukuoka Prefecture, Japan (20). A total of 5,131 patients with diabetes aged 20 years and older were registered between April 2008 and October 2010. Exclusion criteria for the registry included the following: 1) patients with drug-induced diabetes or those undergoing corticosteroid treatment; 2) patients undergoing renal replacement therapy; 3) patients with serious diseases other than diabetes, such as advanced malignancies or decompensated liver cirrhosis; and 4) patients unable to visit diabetologists regularly. After excluding 208 participants with type 1 diabetes and 216 premenopausal women, we enrolled the remaining 4,758 participants for baseline examination. Of the baseline participants, 52 participants were excluded from the analysis because they had no follow-up survey regarding bone fractures (32 died, 18 were lost to follow-up, and 2 withdrew before the survey). The Kyushu University Institutional Review Board approved the study, and all participants provided written informed consent.

Clinical Evaluation at Baseline

Information regarding maximum BW, diabetes duration, onset of diabetes, smoking habits, alcohol intake, leisure-time physical activity (LTPA), and history of laser photocoagulation for diabetic retinopathy, coronary heart disease, stroke, and cancer was obtained using a self-administered questionnaire. Menopausal status was defined as self-reported amenorrhea for >1 year. Smoking habits and alcohol intake were classified as either current use or not. BMI was calculated from BW and height. Maximum BMI was calculated from maximum BW and current height at baseline because we did not obtain height at the time of maximum BW. The presence of depressive symptoms was assessed by using the Center for Epidemiologic Studies Depression Scale (CES-D) (21), and participants who scored ≥16 out of 60 points were defined as having depressive symptoms.

The medical records of participants were reviewed for all medications, including pioglitazone, insulin, antihypertension drugs, antidepressants, and anticonvulsants. The LTPA was assessed as MET hours per week using Ainsworth’s methods (22). Participants engaging in sports regularly during their leisure time were defined as the regular exercise group. The dietary survey, including total energy, total protein, calcium, and vitamin D intake, was conducted using a self-administered brief-type diet history questionnaire (BDHQ) (Gender Medical Research, Inc., Tokyo, Japan) regarding the frequency of 58 food items and supplements. The validity of ranking the energy-adjusted intake of many nutrients has previously been studied in an adult Japanese population (23).

Laboratory Measurements

Blood samples were collected by venipuncture, and spot urine samples were obtained. Hemoglobin A1c (HbA1c) levels were assessed by high-performance liquid chromatography (Tosoh Corp., Tokyo, Japan). Serum total adiponectin levels were determined by latex immunonephelometry (Mitsubishi Chemical Medience, Tokyo, Japan). Cystatin C concentrations were measured by latex immunonephelometry (LSI Medience, Tokyo, Japan). Urinary N-terminal telopeptide of type I collagen (uNTx) levels were determined by enzyme immunoassay (Alere Medical, Tokyo, Japan). The estimated glomerular filtration rates (eGFRs) were calculated based on cystatin C (eGFRcys) using the equation proposed by the Japanese Society of Nephrology (24). The eGFRcys was recently reported to be a better predictor of fractures than creatinine-based eGFR (25).

Evaluation of BW Change

Maximum BW was obtained using a self-administered questionnaire. BW loss was calculated by subtracting baseline BW from the maximum BW and expressed as a percentage of the maximum value. BW loss was categorized into four groups: <10% (including those with maximum BW at baseline), 10% to <20%, 20% to <30%, and ≥30%.

Assessment of Fractures

History of fractures was obtained at enrollment, and fractures at any site were assessed annually using a self-administered questionnaire (26). Fragility fractures were defined as fractures occurring at hip and spine sites, as excess mortality has been well described in patients with fractures at these sites (3,4). Although classical major osteoporotic fractures include upper humerus and wrist, we excluded these fractures because they have not been reported to be related to mortality (3,4,27). The primary outcome was the first fragility fractures. The follow-up period was calculated as the time from enrollment to the first fragility fractures, death, or the planned study ending—whichever occurred first. The secondary outcome was the first fracture at any site. The follow-up period was calculated as the time from enrollment to the first fracture at any site, death, or the planned study ending—whichever occurred first.

Statistical Analysis

The trends in the mean values or proportions were tested using the Jonckheere-Terpstra test or Cochran-Armitage test as appropriate. Differences in the mean values or proportions were tested by Student t test or χ2 test as appropriate. Incidence of the first incident fractures was calculated according to the BW loss group, using the person-years method, and adjusted for age and sex by the direct method using 10-year age-groups for all participants, men, and postmenopausal women, respectively. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% CIs for the first incident fractures. In the multivariable-adjusted model, the following covariates known to be potential risk or protective factors for fractures were selected: age, sex, diabetes duration, current smoking habits, current drinking habits, daily calcium intake, LTPA, HbA1c, eGFRcys, history of photocoagulation, cancer, fragility fractures, and use of pioglitazone. Since previous studies have reported that the relationship between BMI and fractures is nonlinear (28), we performed adjustment for BMI by tertile (tertile one <21.9 kg/m2, tertile two 21.9–25.0 kg/m2, and tertile three >25.0 kg/m2 for postmenopausal women and tertile one <22.1 kg/m2, tertile two 22.1–24.5 kg/m2, and tertile three >24.5 kg/m2 for men). The effect of the interaction between BW loss and other confounding factors on fracture risk was examined by adding an interaction term to the statistical model. All statistical analyses were performed with SAS, version 9.3 (SAS Institute, Cary, NC). Values of P < 0.05 were considered statistically significant in all analyses.

Table 1 summarizes the baseline characteristics of all participants according to the BW loss group. The mean age, duration of diabetes, maximum BMI, calcium intake, vitamin D intake, LTPA, serum adiponectin, and uNTx; proportion of current smokers; and history of photocoagulation for retinopathy, fragility fractures, and cancer increased significantly in participants with greater BW loss. Conversely, the mean onset of diabetes, BMI, total energy intake, HbA1c, and eGFRcys and proportion of current drinkers, pioglitazone use, and antihypertension drug use decreased significantly in participants with greater BW loss. No participants underwent bariatric surgery.

Table 1

Clinical characteristics of all participants according to weight-loss group


Percentage of weight loss
P
<1010 to <2020 to <30≥30
N 2,014 1,852 699 141  
Age (years) 65.7 ± 9.1 66.3 ± 9.3 67.1 ± 9.7 67.6 ± 10.7 <0.001 
Female sex  42.5 41.1 40.3 37.6 0.15 
Men aged <50 years  4.6 4.7 4.4 7.8 0.42 
Duration of diabetes (years) 14.9 ± 10.1 15.7 ± 10.4 17.7 ± 11.2 20.6 ± 12.4 <0.001 
Onset of diabetes (years) 50.3 ± 11.7 50.2 ± 11.3 48.9 ± 12.0 46.5 ± 12.7 0.002 
BMI (kg/m225.0 ± 3.7 23.2 ± 3.1 21.8 ± 3.2 20.5 ± 3.2 <0.001 
Maximum BMI (kg/m226.3 ± 3.8 27.1 ± 3.6 28.6 ± 4.4 31.6 ± 5.7 <0.001 
Current smoker  16.9 18.7 21.2 24.8 0.002 
Current drinker  43.0 38.7 34.9 31.9 <0.001 
Depressive symptoms  8.6 7.0 9.4 7.1 0.80 
Total energy intake (kcal/day) 1,716 ± 495 1,691 ± 494 1,668 ± 481 1,677 ± 531 0.02 
Total protein intake (g/day) 67.5 ± 23.8 67.7 ± 24.3 68.0 ± 24.9 69.5 ± 27.6 0.68 
Calcium intake (mg/1,000 kcal) 316 ± 101 332 ± 102 342 ± 106 345 ± 110 <0.001 
Vitamin D intake (μg/1,000 kcal) 9.5 ± 5.7 9.6 ± 5.9 10.1 ± 6.3 10.6 ± 6.2 0.009 
Supplement use  28.6 26.9 25.2 27.0 0.10 
LTPA (MET h/week) 10.4 ± 13.9 12.9 ± 15.3 13.6 ± 17.0 12.6 ± 15.7 <0.001 
HbA1c (%) 7.5 ± 1.0 7.4 ± 1.0 7.3 ± 1.1 7.2 ± 1.1 <0.001 
HbA1c (mmol/mol) 58.8 ± 10.8 57.3 ± 11.3 55.9 ± 12.3 55.5 ± 11.6 <0.001 
Serum adiponectin (μg/mL) 10.3 ± 7.8 10.8 ± 7.8 12.9 ± 9.0 15.0 ± 8.2 <0.001 
eGFRcys (mL ⋅ min−1 ⋅ 1.73 m−282.3 ± 22.6 83.1 ± 23.2 78.6 ± 25.3 74.3 ± 26.2 0.003 
uNTx (nmol BCE/mmol Cr) 38.1 ± 22.4 41.6 ± 25.0 42.9 ± 24.5 48.0 ± 32.3 <0.001 
History of PC for retinopathy  18.8 20.6 30.3 36.2 <0.001 
History of CHD  14.4 14.3 13.9 12.1 0.55 
History of stroke  10.0 10.5 12.0 12.8 0.10 
History of fragility fracture  2.2 3.4 3.4 5.7 0.006 
History of cancer  8.4 9.9 11.7 13.5 0.002 
Pioglitazone use  17.7 10.8 6.0 6.4 <0.001 
Insulin therapy  29.8 25.4 30.8 31.9 0.88 
Antihypertension drug use  59.6 51.1 52.7 48.2 <0.001 
Antidepressant use  2.3 2.0 2.2 1.4 0.47 
Anticonvulsant use  1.2 0.8 2.2 0.7 0.41 

Percentage of weight loss
P
<1010 to <2020 to <30≥30
N 2,014 1,852 699 141  
Age (years) 65.7 ± 9.1 66.3 ± 9.3 67.1 ± 9.7 67.6 ± 10.7 <0.001 
Female sex  42.5 41.1 40.3 37.6 0.15 
Men aged <50 years  4.6 4.7 4.4 7.8 0.42 
Duration of diabetes (years) 14.9 ± 10.1 15.7 ± 10.4 17.7 ± 11.2 20.6 ± 12.4 <0.001 
Onset of diabetes (years) 50.3 ± 11.7 50.2 ± 11.3 48.9 ± 12.0 46.5 ± 12.7 0.002 
BMI (kg/m225.0 ± 3.7 23.2 ± 3.1 21.8 ± 3.2 20.5 ± 3.2 <0.001 
Maximum BMI (kg/m226.3 ± 3.8 27.1 ± 3.6 28.6 ± 4.4 31.6 ± 5.7 <0.001 
Current smoker  16.9 18.7 21.2 24.8 0.002 
Current drinker  43.0 38.7 34.9 31.9 <0.001 
Depressive symptoms  8.6 7.0 9.4 7.1 0.80 
Total energy intake (kcal/day) 1,716 ± 495 1,691 ± 494 1,668 ± 481 1,677 ± 531 0.02 
Total protein intake (g/day) 67.5 ± 23.8 67.7 ± 24.3 68.0 ± 24.9 69.5 ± 27.6 0.68 
Calcium intake (mg/1,000 kcal) 316 ± 101 332 ± 102 342 ± 106 345 ± 110 <0.001 
Vitamin D intake (μg/1,000 kcal) 9.5 ± 5.7 9.6 ± 5.9 10.1 ± 6.3 10.6 ± 6.2 0.009 
Supplement use  28.6 26.9 25.2 27.0 0.10 
LTPA (MET h/week) 10.4 ± 13.9 12.9 ± 15.3 13.6 ± 17.0 12.6 ± 15.7 <0.001 
HbA1c (%) 7.5 ± 1.0 7.4 ± 1.0 7.3 ± 1.1 7.2 ± 1.1 <0.001 
HbA1c (mmol/mol) 58.8 ± 10.8 57.3 ± 11.3 55.9 ± 12.3 55.5 ± 11.6 <0.001 
Serum adiponectin (μg/mL) 10.3 ± 7.8 10.8 ± 7.8 12.9 ± 9.0 15.0 ± 8.2 <0.001 
eGFRcys (mL ⋅ min−1 ⋅ 1.73 m−282.3 ± 22.6 83.1 ± 23.2 78.6 ± 25.3 74.3 ± 26.2 0.003 
uNTx (nmol BCE/mmol Cr) 38.1 ± 22.4 41.6 ± 25.0 42.9 ± 24.5 48.0 ± 32.3 <0.001 
History of PC for retinopathy  18.8 20.6 30.3 36.2 <0.001 
History of CHD  14.4 14.3 13.9 12.1 0.55 
History of stroke  10.0 10.5 12.0 12.8 0.10 
History of fragility fracture  2.2 3.4 3.4 5.7 0.006 
History of cancer  8.4 9.9 11.7 13.5 0.002 
Pioglitazone use  17.7 10.8 6.0 6.4 <0.001 
Insulin therapy  29.8 25.4 30.8 31.9 0.88 
Antihypertension drug use  59.6 51.1 52.7 48.2 <0.001 
Antidepressant use  2.3 2.0 2.2 1.4 0.47 
Anticonvulsant use  1.2 0.8 2.2 0.7 0.41 

Data are means ± SD or percentages unless otherwise indicated. BCE, bone collagen equivalents; CHD, coronary heart disease; Cr, urinary creatinine; PC, photocoagulation.

From baseline to the end of follow-up (median 5.3 years and follow-up rate 97.6%), 198 participants sustained fragility fractures (54 in hip and 144 in spine). When the accuracy of the self-administered questionnaire was evaluated in 455 fracture events (including 127 fragility fractures) using comparison with medical records, the agreement rate was 93.0%. Figure 1 displays the age- and sex-adjusted incidence of fragility fractures according to the BW loss group in all participants (Fig. 1A), men (Fig. 1B), and postmenopausal women (Fig. 1C). The age- and sex-adjusted incidence rates of fragility fractures were significantly higher with the greater BW loss group in all participants and men (P for trend <0.001 and <0.001, respectively). A similar but nonsignificant trend was observed in postmenopausal women (P for trend 0.06).

Figure 1

Age- and sex-adjusted incidence of fragility fracture according to the groups with BW loss in all participants (A), men (B), and postmenopausal women (C). *P < 0.05, †P < 0.01, ‡P < 0.001 vs. the reference group (weight loss <10%).

Figure 1

Age- and sex-adjusted incidence of fragility fracture according to the groups with BW loss in all participants (A), men (B), and postmenopausal women (C). *P < 0.05, †P < 0.01, ‡P < 0.001 vs. the reference group (weight loss <10%).

Close modal

Table 2 shows the HRs and 95% CIs for fragility fractures according to the BW loss groups and per 10% of BW loss. Age- and sex-adjusted HRs of the greatest BW loss group for fragility fractures compared with the reference group were 3.22 (1.85–5.60) in all participants, 6.63 (2.88–15.27) in men, and 2.17 (1.02–4.65) in postmenopausal women. After multivariate adjustment, the significance remained in all participants and men, whereas the significance diminished in postmenopausal women. Age- and sex-adjusted HRs per 10% of BW loss for fragility fractures were 1.35 (1.16–1.58) in all participants, 1.74 (1.34–2.26) in men, and 1.21 (0.99–1.46) in postmenopausal women.

Table 2

Adjusted HRs (95% CI) for fragility fractures according to weight loss in all participants, men, and postmenopausal women with type 2 diabetes

Weight lossnUnadjusted modelAge- and sex-adjusted modelMultivariate-adjusted model
All participants 4,706    
 <10% 2,014 1.0 (ref.) 1.0 (ref.) 1.0 (ref.) 
 10% to <20% 1,852 1.29 (0.92–1.80) 1.22 (0.87–1.70) 1.24 (0.88–1.76) 
 20% to <30% 699 2.03 (1.38–2.99) 1.75 (1.18–2.57) 1.77 (1.17–2.69) 
 ≥30% 141 4.12 (2.38–7.13) 3.22 (1.85–5.60) 2.84 (1.55–5.21) 
 Per 10%  1.47 (1.26–1.72) 1.35 (1.16–1.58) 1.32 (1.12–1.56) 
Men 2,755    
 <10% 1,159 1.0 (ref.) 1.0 (ref.) 1.0 (ref.) 
 10% to <20% 1,091 1.40 (0.76–2.58) 1.37 (0.74–2.53) 1.48 (0.79–2.77) 
 20% to <30% 417 2.70 (1.39–5.24) 2.43 (1.25–4.72) 2.23 (1.08–4.64) 
 ≥30% 88 6.63 (2.88–15.27) 6.63 (2.88–15.27) 5.20 (2.15–12.57) 
 Per 10%  1.79 (1.38–2.32) 1.74 (1.34–2.26) 1.60 (1.22–2.11) 
Postmenopausal women 1,951    
 <10% 855 1.0 (ref.) 1.0 (ref.) 1.0 (ref.) 
 10% to <20% 761 1.27 (0.85–1.89) 1.17 (0.78–1.75) 1.19 (0.78–1.82) 
 20% to <30% 282 1.79 (1.10–2.89) 1.49 (0.92–2.41) 1.62 (0.96–2.73) 
 ≥30% 53 3.26 (1.54–6.92) 2.17 (1.02–4.65) 1.97 (0.84–4.62) 
 Per 10%  1.34 (1.11–1.63) 1.21 (0.99–1.46) 1.21 (0.98–1.50) 
Weight lossnUnadjusted modelAge- and sex-adjusted modelMultivariate-adjusted model
All participants 4,706    
 <10% 2,014 1.0 (ref.) 1.0 (ref.) 1.0 (ref.) 
 10% to <20% 1,852 1.29 (0.92–1.80) 1.22 (0.87–1.70) 1.24 (0.88–1.76) 
 20% to <30% 699 2.03 (1.38–2.99) 1.75 (1.18–2.57) 1.77 (1.17–2.69) 
 ≥30% 141 4.12 (2.38–7.13) 3.22 (1.85–5.60) 2.84 (1.55–5.21) 
 Per 10%  1.47 (1.26–1.72) 1.35 (1.16–1.58) 1.32 (1.12–1.56) 
Men 2,755    
 <10% 1,159 1.0 (ref.) 1.0 (ref.) 1.0 (ref.) 
 10% to <20% 1,091 1.40 (0.76–2.58) 1.37 (0.74–2.53) 1.48 (0.79–2.77) 
 20% to <30% 417 2.70 (1.39–5.24) 2.43 (1.25–4.72) 2.23 (1.08–4.64) 
 ≥30% 88 6.63 (2.88–15.27) 6.63 (2.88–15.27) 5.20 (2.15–12.57) 
 Per 10%  1.79 (1.38–2.32) 1.74 (1.34–2.26) 1.60 (1.22–2.11) 
Postmenopausal women 1,951    
 <10% 855 1.0 (ref.) 1.0 (ref.) 1.0 (ref.) 
 10% to <20% 761 1.27 (0.85–1.89) 1.17 (0.78–1.75) 1.19 (0.78–1.82) 
 20% to <30% 282 1.79 (1.10–2.89) 1.49 (0.92–2.41) 1.62 (0.96–2.73) 
 ≥30% 53 3.26 (1.54–6.92) 2.17 (1.02–4.65) 1.97 (0.84–4.62) 
 Per 10%  1.34 (1.11–1.63) 1.21 (0.99–1.46) 1.21 (0.98–1.50) 

Multivariate adjustments include age; sex; BMI tertile; diabetes duration; current smoking habit; current drinking habit; daily calcium intake; LTPA; HbA1c; eGFRcys; history of photocoagulation for retinopathy, cancer, or fragility fractures; and pioglitazone use. ref., reference.

Figure 2 shows the interaction analyses between BW loss and possible confounding factors on the fracture risk. A significant interaction was observed between men and postmenopausal women (P for interaction = 0.02). There were no significant interactions between older age (≥70 years), duration of diabetes (≥15 years), obesity (BMI ≥25 kg/m2), history of obesity (maximum BMI ≥25 kg/m2), or regular exercise.

Figure 2

Multivariate-adjusted HR and 95% CIs for fragility fractures per 10% of BW loss from maximum weight, stratified by age; sex; duration of diabetes; BMI; maximum BMI; and regular exercise. Multivariate adjustments included age; sex; BMI tertile; diabetes duration; current smoking habit; current drinking habit; daily calcium intake; LTPA; HbA1c; eGFRcys; history of photocoagulation for retinopathy, cancer, or fragility fractures; and pioglitazone use.

Figure 2

Multivariate-adjusted HR and 95% CIs for fragility fractures per 10% of BW loss from maximum weight, stratified by age; sex; duration of diabetes; BMI; maximum BMI; and regular exercise. Multivariate adjustments included age; sex; BMI tertile; diabetes duration; current smoking habit; current drinking habit; daily calcium intake; LTPA; HbA1c; eGFRcys; history of photocoagulation for retinopathy, cancer, or fragility fractures; and pioglitazone use.

Close modal

As the secondary outcome, 662 participants sustained fractures at any site (249 in men and 413 in postmenopausal women). Supplementary Fig. 1 displays the age- and sex-adjusted incidence of fractures at any site according to the BW loss group in all participants, men, and postmenopausal women. The age- and sex-adjusted incidence rates of any fracture were significantly higher for the group with greater BW loss in all participants and men (P for trend 0.004 and <0.001, respectively). Supplementary Table 1 shows the HRs and 95% CIs for any fractures according to the groups of BW loss and per 10% of BW loss. Age- and sex-adjusted HRs of the group with greatest BW loss for any fracture compared with the reference group were 2.16 (95% CI 1.53–3.07) in all participants, 2.61 (1.56–4.37) in men, and 1.82 (1.13–2.93) in postmenopausal women. After multivariate adjustment, HRs remained statistically significant in all participants, men, and postmenopausal women, respectively. In the interaction analyses (Supplementary Fig. 2), a significant interaction was observed between levels of obesity (BMI ≥25 kg/m2).

Finally, sensitivity analyses were performed because of potential bias caused by 205 participants whose maximum BW was observed at baseline, 453 participants who had a history of cancer, and 52 excluded participants who were younger and comprised more smokers and more insulin users (Supplementary Table 2). Sensitivity analyses were performed after exclusion of participants whose maximum BW was observed at baseline, leaving 4,501 participants for the analysis (Supplementary Table 3); of those with a history of cancer, leaving 4,253 participants (Supplementary Table 4); of male participants aged <50 years, leaving 4,485 participants (Supplementary Table 5); of those with a current smoking habit, leaving 3,835 participants (Supplementary Table 6); and of those with insulin therapy, leaving 3,374 participants (Supplementary Table 7). The results consistently showed an association between BW loss and bone fractures in men but not in postmenopausal women.

In this prospective study, we demonstrated that greater BW loss from the maximum BW was significantly associated with an increased risk of fragility fractures in patients with type 2 diabetes. Especially in men, this association remained significant even after adjustment for potential confounders including current BMI, duration of diabetes, glycemic control, calcium intake, physical activity, history of cancer, and pioglitazone use. To our knowledge, this is the first prospective study to demonstrate a significant association between BW loss from maximum BW and fracture risk in patients with type 2 diabetes.

In the general population, self-reported BW loss of 10% or more from age 50 years among Caucasian women (aged 67 years or older) and self-reported BW loss of ≥10% from maximum BW among women aged 50–74 years were both associated with an increased risk of hip fracture (9,10). Similarly, a prospective investigation in men (aged 67 years or older) found that self-reported BW loss of ≥10% from age 50 years was associated with an increased risk of hip fracture during 8 years of follow-up (11). With a post hoc analysis from the Women’s Health Initiative Observational Study and Clinical Trials, where 120,566 postmenopausal women aged 50–79 years were followed for 11 years, BW loss was associated with fracture risk at the following sites: upper limb, hip, and central body (hip, pelvis, and spine, respectively) (12). Furthermore, in a recent meta-analysis of eight prospective studies, those who experienced BW loss were more likely to develop hip fracture compared with the reference group of people who maintained a stable BW, with an adjusted relative risk of 1.84 (95% CI 1.45–2.33) (13).

The Action for Health in Diabetes (Look AHEAD) trial recently showed that among patients with type 2 diabetes, fractures associated with frailty were more frequent in the group with BW loss than in the control group (29). However, the percent BW change was not associated with future fracture risk. The larger range of BW loss in our study may explain the difference (mean BW loss 12.4% in our study vs. 3.5% in the control group and 6.0% in the intervention group of the Look AHEAD trial).

The loss of BW may influence the risk of fracture by several mechanisms. First, BW loss decreased BMD in the general population as well as in patients with type 2 diabetes. In the Framingham Osteoporosis Study, BW loss of ≥5% from baseline was associated with decreased BMD at the hip or spine in 567 men and women aged 28–62 years (30). Similarly, in the Osteoporotic Fractures in Men (MrOS) study, BW loss of ≥5% was associated with bone loss at the hip in 1,213 men aged 65 years or older (31). This finding was also found in patients with type 2 diabetes, where intentional BW loss was associated with modest bone loss in the hip (14,15). This bone loss related to BW loss has been considered to be the result of a physiological response to decreased mechanical loading (32). Second, BW loss that accompanies the loss of lean mass may result in decreased muscle strength, decreased physical activity, and increased risk of incident fall (33). Since patients with diabetes have been described to have sarcopenia and physical disability, leading to risks of incident fall (34), the group with greater BW loss in our study may include more patients with sarcopenia. Third, as patients with diabetes undertake diet therapy to improve glycemic control or attenuate obesity, greater BW loss may suggest decreased intake of nutrients such as protein, calcium, and vitamin D, which are reported to play an important role in maintaining bone strength (35,36). However, as shown in Table 1, there was no reduction of intake of these nutrients in the groups with greater BW loss. Finally, previous studies have explained that fracture risk is related to BW loss because of underlying serious medical conditions such as cancer (8,9,12). However, the relationship between BW loss and fracture risk was significant after adjustment for history of cancer and sensitivity analysis (Supplementary Table 4). In addition, we excluded patients with serious diseases such as advanced malignancies or decompensated liver cirrhosis.

The association between BW loss and fragility fracture risk appears to be stronger in men than in postmenopausal women, and there was a significant interaction between men and postmenopausal women for fragility fractures (Fig. 2). Drastic changes in sex hormones may explain this sex difference, given that the incidence rate of fragility fractures was much higher in postmenopausal women than in men. This may reduce the impact of BW loss in postmenopausal women. Furthermore, men lose more muscle mass than women with BW loss, resulting in increased mechanical stress on bone (37). Actually, the 4-year BW loss intervention in the Look AHEAD trial was significantly associated with a modest increase in bone loss at the hip in men but not in women (14).

There was a significant interaction with sex for BW loss and fragility fractures, but this was not the case for any fracture (Fig. 2 and Supplementary Fig. 2). This may be explained by the possibility that “any fracture” may include more fractures derived from excessive external force, which may occur in men more frequently than in postmenopausal women. Furthermore, the association between BW loss and any fracture was insignificant in those with higher BMI (Supplementary Fig. 2), probably because those with higher BMI (≥25 kg/m2) may have greater muscle mass, which may be protective against traumatic fractures, than those with lower BMI (<25 kg/m2). In addition, there was no significant interaction between regular exercise and BW loss on fracture risk (Fig. 2). In a previous intervention trial, resistance training attenuated bone loss along with BW loss in patients with type 2 diabetes (15). However, the amount of exercise may be different between the intervention study and our cohort.

The strength of the current study is the prospective cohort design, with a relatively large number of patients with type 2 diabetes (mean age 66 years), which included adjustment for potential confounders, including diet, physical activity, and medication. Additionally, our study has limitations. First, 52 participants were excluded from the analyses because of a lack of bone fracture information. As shown in Supplementary Table 2, excluded participants were younger and comprised more smokers and more insulin users. However, the sensitivity analyses showed that exclusion of men aged <50 years, smokers, or insulin users did not substantially affect the outcomes of the current study (Supplementary Tables 57). Second, we derived incident fractures from self-reported data, which may result in misclassification, although the accuracy of 455 fracture events was 93.0%. However, since multiple studies have shown that a majority of spine fractures do not present clinically (38), fracture incidence may be underreported. Assuming that the errors in self-reporting do not vary by weight loss categories, the likely impact of this misclassification would be to attenuate any association toward the null. Third, maximum BW was also self-reported. It was reported that BW recalled by elderly persons from many years earlier was fairly accurate (39), although women may be more prone to underestimate their maximum BW than men (39). This bias may have resulted in an underestimation of BW loss and a bias toward the null for association between BW loss and fracture risk. Fourth, 205 participants had their maximum BW at baseline. However, the sensitivity analysis results after exclusion of these participants were almost identical to those before exclusion (Supplementary Table 3). Fifth, we did not evaluate possible external forces causing fractures. Whether fractures were caused by excessive trauma was not known. Sixth, we did not evaluate BMD, incident fall, peripheral neuropathy, or measurement of parathyroid hormone or 25-hydroxyvitamin D, which have been shown to impact fracture risk (35,40). Seventh, since all participants in the current study were Japanese, it remains unclear whether the conclusions of our study can be generalized to other ethnic populations. Finally, because the current study was observational without any controlled, randomized intervention, there may be other confounding factors besides those used in the study.

In conclusion, our study demonstrates that greater BW loss from maximum BW increases future fracture risk in patients with type 2 diabetes, especially in men. Although patients with diabetes often lose weight either intentionally or unintentionally, preventive measures for fragility fractures should be considered in those who lose >20% of the maximum BW.

Acknowledgments. The authors thank Dr. Yutaka Kiyohara, Dr. Yasufumi Doi, Dr. Toshiharu Ninomiya, Dr. Shigenobu Kanba, Dr. Shuzo Kumagai, Dr. Shinako Kaizu, Dr. Yoichiro Hirakawa, Dr. Chisa Matsumoto, and Dr. Chie Kitaoka (Kyushu University); Dr. Nobutaka Tsutsu and Dr. Nobuhiro Sasaki (Fukuoka Red Cross Hospital); Dr. Kiyohide Nunoi, Dr. Yuichi Sato, Dr. Yuji Uchizono, Dr. Ayumi Yamauchi, Dr. Kaori Itoh, and Dr. Chie Kono (St. Mary’s Hospital); Dr. Sakae Nohara, Dr. Hirofumi Imoto, and Dr. Kazushi Amano (Steel Memorial Yawata Hospital); Dr. Daisuke Gotoh, Dr. Toshitaka Himeno, and Dr. Masae Toyonaga (Kyushu Central Hospital); Dr. Noriyasu Shinohara and Dr. Ayako Tsutsumi (Fukuoka Higashi Medical Center); Dr. Yasuhiro Idewaki, Dr. Masahiro Nakano, Dr. Mina Matsuo, Dr. Shoko Morimoto, and Dr. Tomoko Hyodo (Hakujyuji Hospital); Dr. Masae Minami (Clinic Minami Masae); Dr. Miya Wada (Wada Miya Naika Clinic); Dr. Yoshifumi Yokomizo (Yokomizo Naika Clinic); Dr. Masanori Kikuchi and Dr. Yohei Kikuchi (Kikuchi Naika Clinic); Dr. Riku Nomiyama (Suzuki Naika Clinic); Dr. Shin Nakamura (Nakamura Naika Clinic); Dr. Kenji Tashiro (Oshima Eye Hospital); Dr. Mototaka Yoshinari (Yoshinari Naika Clinic); Dr. Kojiro Ichikawa (Fukutsu Naika Clinic); and Dr. Teruo Omae (Hisayama Research Institute For Lifestyle Diseases). The authors also thank clinical research coordinators Chiho Ohba (Hisayama Research Institute For Lifestyle Diseases) and Kayoko Sekioka and Yoko Nishioka (Kyushu University), as well as those in the administration office: Tomoko Matake (Hisayama Research Institute For Lifestyle Diseases) and Junko Ishimatsu (Kyushu University). In addition, the authors thank the Edanz Group (www.edanzediting.com/ac) for editing a draft of this manuscript.

Funding. The Japan Society for the Promotion of Science KAKENHI (grant numbers 23249037 and 23659353 for M.I. and 16K00861 for H.F.) from the Ministry of Education, Culture, Sports, Science and Technology of Japan supported this work in part.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Author Contributions. Y.K. and M.I. were responsible for the study concept and design. Y.K., M.I., and H.F. conducted the analysis, and T.O., H.I., T.J.-K., A.S., M.Y., U.N., D.K., and T.K. interpreted data and contributed to the discussion. Y.K. and M.I. drafted the manuscript. All authors participated in critically revising the manuscript and approved the final version. M.I. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

1.
Janghorbani
M
,
Feskanich
D
,
Willett
WC
,
Hu
F
.
Prospective study of diabetes and risk of hip fracture: the Nurses’ Health Study
.
Diabetes Care
2006
;
29
:
1573
1578
[PubMed]
2.
Schwartz
AV
.
Epidemiology of fractures in type 2 diabetes
.
Bone
2016
;
82
:
2
8
[PubMed]
3.
Cauley
JA
,
Thompson
DE
,
Ensrud
KC
,
Scott
JC
,
Black
D
.
Risk of mortality following clinical fractures
.
Osteoporos Int
2000
;
11
:
556
561
[PubMed]
4.
Center
JR
,
Nguyen
TV
,
Schneider
D
,
Sambrook
PN
,
Eisman
JA
.
Mortality after all major types of osteoporotic fracture in men and women: an observational study
.
Lancet
1999
;
353
:
878
882
[PubMed]
5.
Lecka-Czernik
B
.
Diabetes, bone and glucose-lowering agents: basic biology
.
Diabetologia
2017
;
60
:
1163
1169
[PubMed]
6.
Looker
HC
,
Knowler
WC
,
Hanson
RL
.
Changes in BMI and weight before and after the development of type 2 diabetes
.
Diabetes Care
2001
;
24
:
1917
1922
[PubMed]
7.
Hadden
DR
,
Blair
AL
,
Wilson
EA
, et al
.
Natural history of diabetes presenting age 40-69 years: a prospective study of the influence of intensive dietary therapy
.
Q J Med
1986
;
59
:
579
598
[PubMed]
8.
Cummings
SR
,
Nevitt
MC
,
Browner
WS
, et al.;
Study of Osteoporotic Fractures Research Group
.
Risk factors for hip fracture in white women
.
N Engl J Med
1995
;
332
:
767
773
[PubMed]
9.
Langlois
JA
,
Harris
T
,
Looker
AC
,
Madans
J
.
Weight change between age 50 years and old age is associated with risk of hip fracture in white women aged 67 years and older
.
Arch Intern Med
1996
;
156
:
989
994
[PubMed]
10.
Langlois
JA
,
Mussolino
ME
,
Visser
M
,
Looker
AC
,
Harris
T
,
Madans
J
.
Weight loss from maximum body weight among middle-aged and older white women and the risk of hip fracture: the NHANES I epidemiologic follow-up study
.
Osteoporos Int
2001
;
12
:
763
768
[PubMed]
11.
Langlois
JA
,
Visser
M
,
Davidovic
LS
,
Maggi
S
,
Li
G
,
Harris
TB
.
Hip fracture risk in older white men is associated with change in body weight from age 50 years to old age
.
Arch Intern Med
1998
;
158
:
990
996
[PubMed]
12.
Crandall
CJ
,
Yildiz
VO
,
Wactawski-Wende
J
, et al
.
Postmenopausal weight change and incidence of fracture: post hoc findings from Women’s Health Initiative Observational Study and Clinical Trials
.
BMJ
2015
;
350
:
h25
[PubMed]
13.
Lv
QB
,
Fu
X
,
Jin
HM
, et al
.
The relationship between weight change and risk of hip fracture: meta-analysis of prospective studies
.
Sci Rep
2015
;
5
:
16030
[PubMed]
14.
Lipkin
EW
,
Schwartz
AV
,
Anderson
AM
, et al.;
Look AHEAD Research Group
.
The Look AHEAD trial: bone loss at 4-year follow-up in type 2 diabetes
.
Diabetes Care
2014
;
37
:
2822
2829
[PubMed]
15.
Daly
RM
,
Dunstan
DW
,
Owen
N
,
Jolley
D
,
Shaw
JE
,
Zimmet
PZ
.
Does high-intensity resistance training maintain bone mass during moderate weight loss in older overweight adults with type 2 diabetes
?
Osteoporos Int
2005
;
16
:
1703
1712
[PubMed]
16.
Neal
B
,
Perkovic
V
,
Mahaffey
KW
, et al.;
CANVAS Program Collaborative Group
.
Canagliflozin and cardiovascular and renal events in type 2 diabetes
.
N Engl J Med
2017
;
377
:
644
657
[PubMed]
17.
Watts
NB
,
Bilezikian
JP
,
Usiskin
K
, et al
.
Effects of canagliflozin on fracture risk in patients with type 2 diabetes mellitus
.
J Clin Endocrinol Metab
2016
;
101
:
157
166
[PubMed]
18.
Su
B
,
Sheng
H
,
Zhang
M
, et al
.
Risk of bone fractures associated with glucagon-like peptide-1 receptor agonists’ treatment: a meta-analysis of randomized controlled trials
.
Endocrine
2015
;
48
:
107
115
[PubMed]
19.
Nakamura
KM
,
Haglind
EG
,
Clowes
JA
, et al
.
Fracture risk following bariatric surgery: a population-based study
.
Osteoporos Int
2014
;
25
:
151
158
[PubMed]
20.
Ohkuma
T
,
Fujii
H
,
Iwase
M
, et al
.
Impact of sleep duration on obesity and the glycemic level in patients with type 2 diabetes: the Fukuoka Diabetes Registry
.
Diabetes Care
2013
;
36
:
611
617
[PubMed]
21.
Radloff
LS
.
The CES-D scale: a self-report depression scale for research in the general population
.
Appl Psychol Meas
1977
;
1
:
385
401
22.
Ainsworth
BE
,
Haskell
WL
,
Whitt
MC
, et al
.
Compendium of physical activities: an update of activity codes and MET intensities
.
Med Sci Sports Exerc
2000
;
32
(
Suppl.
):
S498
S504
[PubMed]
23.
Kobayashi
S
,
Honda
S
,
Murakami
K
, et al
.
Both comprehensive and brief self-administered diet history questionnaires satisfactorily rank nutrient intakes in Japanese adults
.
J Epidemiol
2012
;
22
:
151
159
[PubMed]
24.
Horio
M
,
Imai
E
,
Yasuda
Y
,
Watanabe
T
,
Matsuo
S
;
Collaborators Developing the Japanese Equation for Estimated GFR
.
GFR estimation using standardized serum cystatin C in Japan
.
Am J Kidney Dis
2013
;
61
:
197
203
[PubMed]
25.
Ensrud
KE
,
Parimi
N
,
Fink
HA
, et al.;
Osteoporotic Fractures in Men Study Group
.
Estimated GFR and risk of hip fracture in older men: comparison of associations using cystatin C and creatinine
.
Am J Kidney Dis
2014
;
63
:
31
39
[PubMed]
26.
Komorita
Y
,
Iwase
M
,
Fujii
H
, et al
.
Serum adiponectin predicts fracture risk in individuals with type 2 diabetes: the Fukuoka Diabetes Registry
.
Diabetologia
2017
;
60
:
1922
1930
[PubMed]
27.
Johnell
O
,
Kanis
JA
,
Odén
A
, et al
.
Mortality after osteoporotic fractures
.
Osteoporos Int
2004
;
15
:
38
42
[PubMed]
28.
Compston
JE
,
Flahive
J
,
Hosmer
DW
, et al.;
GLOW Investigators
.
Relationship of weight, height, and body mass index with fracture risk at different sites in postmenopausal women: the Global Longitudinal study of Osteoporosis in Women (GLOW)
.
J Bone Miner Res
2014
;
29
:
487
493
[PubMed]
29.
Johnson
KC
,
Bray
GA
,
Cheskin
LJ
, et al.;
Look AHEAD Study Group
.
The effect of intentional weight loss on fracture risk in persons with diabetes: results from the Look AHEAD randomized clinical trial
.
J Bone Miner Res
2017
;
32
:
2278
2287
[PubMed]
30.
Hannan
MT
,
Felson
DT
,
Dawson-Hughes
B
, et al
.
Risk factors for longitudinal bone loss in elderly men and women: the Framingham Osteoporosis Study
.
J Bone Miner Res
2000
;
15
:
710
720
[PubMed]
31.
Ensrud
KE
,
Fullman
RL
,
Barrett-Connor
E
, et al.;
Osteoporotic Fractures in Men Study Research Group
.
Voluntary weight reduction in older men increases hip bone loss: the Osteoporotic Fractures in Men study
.
J Clin Endocrinol Metab
2005
;
90
:
1998
2004
[PubMed]
32.
Edelstein
SL
,
Barrett-Connor
E
.
Relation between body size and bone mineral density in elderly men and women
.
Am J Epidemiol
1993
;
138
:
160
169
[PubMed]
33.
Nevitt
MC
,
Cummings
SR
,
Kidd
S
,
Black
D
.
Risk factors for recurrent nonsyncopal falls: a prospective study
.
JAMA
1989
;
261
:
2663
2668
[PubMed]
34.
Schwartz
AV
,
Hillier
TA
,
Sellmeyer
DE
, et al
.
Older women with diabetes have a higher risk of falls: a prospective study
.
Diabetes Care
2002
;
25
:
1749
1754
[PubMed]
35.
Dawson-Hughes
B
,
Harris
SS
,
Krall
EA
,
Dallal
GE
.
Effect of calcium and vitamin D supplementation on bone density in men and women 65 years of age or older
.
N Engl J Med
1997
;
337
:
670
676
[PubMed]
36.
Orwoll
E
,
Ware
M
,
Stribrska
L
, et al
.
Effects of dietary protein deficiency on mineral metabolism and bone mineral density
.
Am J Clin Nutr
1992
;
56
:
314
319
[PubMed]
37.
Pocock
N
,
Eisman
J
,
Gwinn
T
, et al
.
Muscle strength, physical fitness, and weight but not age predict femoral neck bone mass
.
J Bone Miner Res
1989
;
4
:
441
448
[PubMed]
38.
Ettinger
B
,
Black
DM
,
Nevitt
MC
, et al.;
The Study of Osteoporotic Fractures Research Group
.
Contribution of vertebral deformities to chronic back pain and disability
.
J Bone Miner Res
1992
;
7
:
449
456
[PubMed]
39.
Perry
GS
,
Byers
TE
,
Mokdad
AH
,
Serdula
MK
,
Williamson
DF
.
The validity of self-reports of past body weights by U.S. adults
.
Epidemiology
1995
;
6
:
61
66
[PubMed]
40.
Kanis JA; World Health Organization Scientific Group. Assessment of osteoporosis at the primary health-care level. Technical Report. World Health Organization Collaborating Centre for Metabolic Bone Diseases, University of Sheffield, Sheffield, U.K., 2007
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Supplementary data