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Original Article
Correlation of bone mineral density with ankle fractures in older adults in Korea: a retrospective cohort study
Seung Hyun Lee1orcid, Chae Hun Lee1orcid, Seo Jin Park2orcid, Jun Young Lee1orcid
Journal of Musculoskeletal Trauma 2025;38(4):186-192.
DOI: https://doi.org/10.12671/jmt.2025.00150
Published online: October 24, 2025

1Department of Orthopedic Surgery, Chosun University Hospital, Gwangju, Korea

2Department of Nursing Science, Gwangju University, Gwangju, Korea

Correspondence to: Jun Young Lee, Department of Orthopedic Surgery, Chosun University Hospital, 365 Pilmun-daero, Dong-gu, Gwangju, Korea Tel: +82-62-220-3147 Email: leejy88@chosun.ac.kr
• Received: March 10, 2025   • Revised: August 1, 2025   • Accepted: August 8, 2025

© 2025 The Korean Orthopaedic Trauma Association

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Background
    Bone mineral density (BMD) is well-documented in relation to fractures of the spine, hip, distal radius, and proximal humerus; however, its correlations with other fracture types are less established. This study aimed to analyze BMD and associated risk factors in older adults (≥65 years of age) with osteoporotic ankle fractures. These fractures involve low-energy trauma, resulting from falls from a standing height or lower, and occur from impacts which typically do not cause fractures in individuals with normal bone.
  • Methods
    This retrospective study analyzed data from 1,411 patients diagnosed with ankle fractures admitted to Chosun University Hospital between February 2012 and April 2023. After applying inclusion criteria (age ≥65 years; low energy ankle fracture) and exclusion criteria (high energy trauma, open/multiple fractures, missing dual X-ray absorptiometry [DXA]), 73 of 1,411 patients were analyzed. Lumbar spine, femoral neck, and total hip T scores were obtained with a Horizon Wi DXA scanner, and associations with age, sex, mechanism of injury, comorbidities, smoking status, alcohol consumption, body mass index (BMI), and history of fractures were tested by ANOVA with Scheffe post hoc and Fisher exact tests.
  • Results
    Lower BMD correlated significantly with older age, female sex, and lower BMI (P<0.05) in older adults with ankle fractures. No significant associations were observed for comorbidities (diabetes, hypertension, dementia), smoking, alcohol consumption, injury mechanism, or prior fractures.
  • Conclusion
    These results indicate that older age, female, and lower BMI are linked to reduced BMD in ankle fracture patients over 65 years of age. Focused osteoporosis screening and management may therefore be most beneficial for older, low BMI women presenting with ankle fractures.
  • Level of evidence
    Level 4
  • Keywords: Bone density, Ankle fractures, Aged
Background
Osteoporosis is the most common metabolic bone disease in old age, and with the rapid increase in the elderly population, understanding and preventing the related factors is important. A previous history of osteoporotic fractures is a significant predictor of new fractures, making early and accurate diagnosis of osteoporotic fractures crucial [1].
Currently, bone mineral density (BMD) is primarily measured in the spine and hip, and a lower BMD value indicates a higher risk of fractures in the spine and hip [2]. Low BMD is a well established risk factor for osteoporotic fractures of the spine, hip (including femoral neck and intertrochanteric fractures), distal radius, and proximal humerus, however, its correlation with other fracture types is less established [3,4]. In particular, while the incidence of ankle fractures increases in postmenopausal women [5,6], some studies suggest that ankle fractures may have a weaker association with osteoporosis [7]. This has led to ongoing research [8] to further investigate the relationship.
Objectives
This study aims to analyze BMD and its associated risk factors in elderly patients (65 years and older) with osteoporotic ankle fractures. These fractures typically result from low‐energy trauma, such as falls from a standing height or lower, which generally do not cause fractures in individuals with normal bone [9]. Various factors are known to influence BMD, including age, sex, physical activity level, smoking, alcohol consumption, and body weight [10]. Indeed, several studies have shown that higher body weight is correlated with higher BMD and may lower the incidence of hip fractures [10,11]. Building on these findings, the present study examines whether these factors also play a role in ankle fractures among the elderly and seeks to clarify the relationship between low BMD and the ankle fractures in this population.
Ethics statement
It was approved by the institutional review board (IRB) of the Chosun University Hospital (IRB No. 2024-10-025).
Study design
It is a retrospective cohort study based on the electronic medical records of the hospital.
Setting
From February 2012 to April 2023, a total of 1,411 patients were admitted to Chosun University Hospital with ankle fractures. Their electronic medical records were analyzed.
Participants
The inclusion criteria for this study were: age ≥65 years, a single ankle fracture sustained from low-energy trauma (e.g., a fall from standing height or lower), and availability of BMD data. Therefore, we excluded 430 patients who had open fractures, multiple fractures, or experienced high-energy trauma (e.g., a fall from a height >1.5 m or traffic accidents). Among the remaining patients, 87 met the age criterion (≥65 years), but 14 had not undergone BMD testing. Consequently, a total of 73 patients were included in the final analysis.
Variables
Primary outcome variables were BMD of the lumbar spine, femoral neck, and total hip. Predictor/explanatory variables were age, sex, injury mechanism, comorbidities, lifestyle factors (smoking, alcohol drinking), BMI, and fracture history.
Data sources/measurement
BMD was measured at lumbar spine, femoral neck, and total hip using a Horizon Wi dual-energy X-ray absorptiometry (DXA) scanner (Hologic Inc., USA), following the manufacturer’s recommended protocols.
Patients were categorized by age into three groups: ≤69 years (group a), 70–79 years (group b), and ≥80 years (group c). The mechanism of injury was classified into low-energy injuries corresponding to osteoporotic fractures, such as twisting injury, slip down, falls from a standing height or less, or other types of injuries. Comorbidities were classified based on the presence of diabetes, hypertension, and dementia, which are highly prevalent in the elderly. BMD was categorized according to World Health Organization criteria, with T scores defined as normal (>–1.0), osteopenia (–1.0 to –2.5), and osteoporosis (≤ –2.5). Smoking status was divided into smokers and non-smokers, while alcohol consumption was classified as drinking if the intake was 3 units or more per day (with one unit representing 8–10 grams of alcohol, roughly equivalent to a standard glass of beer (285 mL), a single measure of spirits (30 mL), a medium-sized glass of wine (120 mL), or 1 measure of an aperitif (60 mL) and non-drinking otherwise. Body mass index (BMI) was classified according to Korea standards into normal weight (18.5–22.9), overweight (23–24.9), obesity (25–29.9), and severe obesity (≥30.0). Lastly, patients were categorized based on a history of previous fractures.
Bias
Potential confounders such as medication use (e.g., corticosteroids, osteoporosis treatment), nutritional status, vitamin D levels, physical activity, and socioeconomic status were not controlled for. Their omission may impact associations between BMD and the studied risk factors. Sex distribution (61.6% women) may confound observed associations between age and BMD.
Study size
All included subjects were analyzed; therefore, no sample size calculation was performed.
Statistical methods
Data were analyzed using IBM SPSS ver. 27.0 (IBM Corp.). Descriptive statistics were used to analyze general characteristics and fracture-related risk factors of the study subjects. To identify differences in BMD across these characteristics, ANOVA was performed. Post-hoc analysis was conducted using the Scheffe test, and Fisher exact test was used for cells with frequencies less than 5.
A total of 73 patients (mean age, 71.6±5.8 years) were included, of whom 28 (38.4%) were male and 45 (61.6%) were female. Most ankle fractures resulted from low-energy mechanisms such as twisting injuries (38.4%) or slip-down events (54.8%), and nearly half the patients (53.4%) had osteoporosis based on BMD T-scores. Detailed demographic and clinical characteristics, including comorbidities, smoking/alcohol status, and BMI categories, are presented in Table 1.
The mean BMD of the total patients was –2.40±1.00. Specifically, –1.96±1.41 for the spine T-score, –1.80±0.99 for the hip-neck T-score, and –1.19±0.95 for the total hip T-score. The study revealed a statistically significant difference in mean BMD among the age groups (P=0.023), with post-hoc testing indicating a significant difference between the group a (≤69 years) and group b (70–79 years). Regarding spine T-score, ANOVA analysis also showed a difference among the groups (P=0.030), and post-hoc testing confirmed a significant difference between the group a (≤69 years) and group b (70–79 years). Group a (≤69 years) and group c (≥80 years) did not reach statistical significance in post-hoc test. This may be due to the small sample size in the group c, which can limit statistical power and obscure true differences. Hip neck T-score and total hip T-score also differed across age (P=0.014 and P=0.009, respectively). By sex, the mean BMD was −2.09±0.92 in males and −2.58±1.01 in females, indicating a statistically significant difference (P=0.040), and both spine and total hip T-scores also showed differences (P=0.038 and P=0.024, respectively). In BMI classification, the mean BMD was −2.91±0.97 in the normal-weight group, −1.92±1.21 in the overweight group, −2.35±0.75 in the obese group, and −2.13±0.96 in the severely obese group. ANOVA analysis revealed a statistically significant difference among these groups (P=0.017), with post-hoc testing indicating a significant difference between the normal-weight and overweight groups. Also, the total hip T-score showed a difference among these groups (P=0.039). In injury mechanisms, comorbidities, smoking status, alcohol consumption and previous fracture history groups, none of these differences were statistically significant. In the case of dementia, only one patient (n=1) in our study had this condition, rendering any statistical comparison or interpretation of BMD differences in that subgroup highly limited. Therefore, we opted to include this variable for completeness but acknowledge that no meaningful conclusions can be drawn from such a small sample (Table 2).
Key results
Our study demonstrated that older age, females, and lower BMI were significantly associated with lower BMD in elderly patients with ankle fractures, whereas comorbidities (including diabetes, hypertension, dementia), smoking, alcohol consumption, injury mechanism, and previous fracture history did not show a notable impact.
Interpretation/comparison with previous studies
Although our study did not directly measure peripheral BMD at the ankle joint, a previous study [12] analyzed the correlation between central BMD (spine and hip) and peripheral BMD (medial cartilage, distal tibia, lateral cartilage, and talus) using DXA, reporting a significant association across all measurement sites. Such findings imply that assessing BMD at or around the ankle may be useful for identifying high-risk patients. While our analysis focused on central BMD, these prior results suggest a potential linkage between central and peripheral bone measurements that warrants further direct evaluation in future studies.
Many studies indicate that higher body weight can provide a protective effect on bone through appropriate mechanical loading [13]. Also, a recent systematic review and meta-analysis found that obesity is generally associated with higher areal BMD, yet the overall fracture risk pattern is heterogeneous, weight bearing sites may benefit from greater mechanical loading, whereas non weight bearing or peripheral sites can still experience increased fracture risk [14]. Our study suggests that lower BMI in elderly patients with ankle fractures was associated with lower BMD. However, obesity has been reported to have a negative impact on BMD due to systemic inflammatory responses, which may be harmful to bones. Furthermore, increased bone marrow adipogenesis in obese individuals may contribute to reduced bone mass [13]. A recent study suggested that the relationship between body weight and BMD follows an inverted U-shaped pattern [15]. In this study, lower BMD was observed in underweight individuals, with BMD increasing up to a certain threshold, beyond which excessive obesity was associated with a decline in BMD. This pattern may help explain the complex relationship between BMD and body weight. Therefore, in our study, classification based solely on body weight likely led to the inclusion of a majority of older and female patients in the low BMI group, which consequently exhibited lower BMD. Although some ankle fracture studies have linked high BMI to fracture risk [16,17], our study focuses on BMD rather than fracture incidence, suggesting that BMI may modulate bone quality differently from its effect on fall mechanics. These findings highlight the complexity of the relationship between ankle fractures and BMD, which cannot be explained by a single factor. Given the ongoing debates and investigations in this area, further studies are needed to clarify these associations.
One might intuitively assume that patients with diabetes would exhibit lower BMD due to impaired bone metabolism. However, recent studies suggest that individuals with type 2 diabetes often have normal or even slightly higher BMD compared to non-diabetic controls, despite an overall increased risk of fractures [18,19]. This apparent paradox has been attributed to factors such as the accumulation of advanced glycation end-products, alterations in bone microarchitecture, and the potential confounding effect of higher BMI in many patients with type 2 diabetes [20]. In other words, even when BMD measurements appear preserved or elevated, qualitative changes in bone tissue and a heightened propensity for falls may collectively raise fracture risk. Our finding of relatively higher BMD among diabetic patients aligns with these reports, underscoring the need to interpret BMD values in the context of broader clinical and metabolic factors.
Limitation
A key limitation of this study is its retrospective design at a single institution, coupled with a relatively small sample size, which may restrict the generalizability of our findings. The small sample size also likely contributed to some unexpected observations. For example, although BMD T-scores decreased with advancing age, this trend might be confounded by the higher proportion of female patients in the oldest group. Postmenopausal women typically show a steeper decline in bone mass, suggesting that the observed age-related decrease may partly reflect sex differences rather than aging alone. Additionally, our data revealed that non-smokers and non-drinkers had slightly lower BMD contrary to most established reports [21,22]. Such discrepancies are likely influenced by limited statistical power and potential confounders like medication use, lifestyle factors and other unmeasured variables.
Suggestion for further studies
Future studies should therefore involve larger, more diverse populations and incorporate detailed individual factors to clarify these trends and strengthen the understanding of the relationship between BMD and ankle fractures.
Conclusion
In conclusion, lower BMD in elderly patients (≥65 years) with low energy ankle fractures is associated with older age, female sex, and lower BMI. These findings highlight the importance of assessing BMD and osteoporosis assessment, particularly in ankle fracture patients who have these characteristics.

Author contribution

Conceptualization: SHL, CHL, JYL. Data curation: SHL, CHL, SJP. Funding: JYL. Formal analysis: SHL, JYL. Methodology: SHL, SJP, JYL. Project administration: JYL. Investigation: SHL, CHL. Supervision: JYL, SJP. Writing-original draft: SHL, CHL, SJP, JYL. Writing-review & editing: SHL, CHL, SJP, JYL. All authors read and approved the final manuscript.

Conflict of interests

No potential conflict of interest relevant to this article was reported.

Funding

This study was supported by research fund from Chosun University 2023.

Data availability

Contact the corresponding author for data availability.

Acknowledgments

None.

Supplementary materials

None.

Table 1.
Demographics of the patients (n=73)
Variable Value
Age (yr) 71.64±5.74
 ≤69 31 (42.5)
 70‒79 33 (45.2)
 ≥80 9 (12.3)
Sex (male:female) 28 (38.4):45 (61.6)
Injury mechanism
 Twisting injury 28 (38.4)
 Slip down 40 (54.8)
 Fall down 3 (4.1)
 Other 2 (2.7)
Comorbidity (no:yes)
 Diabetes 46 (63):27 (37)
 Hypertension 35 (47.9):38 (52.1)
 Dementia 72 (98.6):1 (1.4)
Bone mineral density
 Normal 7 (9.7)
 Osteopenia 27 (37)
 Osteoporosis 39 (53.4)
Health behavior (no:yes)
 Smoking 67 (91.8):6 (8.2)
 Alcohol 69 (94.5):4 (5.5)
Body mass index (kg/m²) 24.89±3.16
 Normal 21 (28.8)
 Overweight 17 (23.3)
 Obese 31 (42.5)
 Severely obese 4 (5.5)
Previous fracture history (no:yes) 59 (80.8):14 (19.2)

Values are presented as mean±standard deviation or number (%).

Table 2.
Associations between bone mineral density (BMD) and patients’ characteristics (n=73)
Variable Category BMD
 Spine T-score
 Hip neck T-score
 Total hip T-score
Mean±SD t/F P-value Mean±SD t/F P-value Mean±SD t/F P-value Mean±SD t/F P-value
Total ‒2.40±1.00 ‒1.96±1.41 ‒1.80±0.99 ‒1.19±0.95
Age (yr) ≤69a ‒2.09±0.84 3.967 0.023 (a>b) ‒1.62±1.24 3.697 0.03 (a>b) ‒1.55±0.98 4.508 0.014 (a>c) ‒0.92±0.93 5.015 0.009 (a>c)
70‒79b ‒2.56±1.08 ‒2.36±1.29 ‒1.82±1.00 ‒1.26±0.95
≥80c ‒2.87±0.97 ‒1.66±2.08 ‒2.58±0.45 ‒1.87±0.71
Sex Male ‒2.09±0.92 2.088 0.040 ‒1.53±1.51 2.117 0.038 ‒1.59±0.98 1.474 0.145 ‒0.87±1.00 2.299 0.024
Female ‒2.58±1.01 ‒2.23±1.30 ‒1.93±0.98 ‒1.38±0.88
Injury mechanism Twisting injury ‒2.38±0.80 2.003 0.122 ‒2.12±1.25 1.871 0.143 ‒1.63±0.96 1.279 0.288 ‒1.04±0.85 0.980 0.407
Slip down ‒2.28±1.06 ‒1.69±1.44 ‒1.82±1.02 ‒1.22±1.02
Fall down ‒3.40±0.56 ‒3.37±0.60 ‒2.53±0.32 ‒1.80±0.30
Other ‒3.45±2.19 ‒2.80±3.11 ‒2.60±0.99 ‒1.85±1.63
Comorbidity Diabetes No ‒2.55±1.02 1.793 0.077 ‒2.13±1.53 1.343 0.184 ‒1.84±1.04 0.317 0.752 ‒1.25±1.01 0.675 0.502
Yes ‒2.13±0.93 ‒1.67±1.16 ‒1.75±0.90 ‒1.09±0.86
Hypertension No ‒2.37±1.11 0.176 0.861 ‒2.11±1.35 0.883 0.380 ‒1.63±1.14 1.384 0.171 ‒1.03±1.09 1.376 0.173
Yes ‒2.42±0.90 ‒1.82±1.48 ‒1.95±0.81 ‒1.33±0.79
Dementia No ‒2.39±1.01 0.204 0.839 ‒1.95±1.42 0.383 0.703 ‒1.79±0.99 0.814 0.419 ‒1.19±0.96 0.013 0.99
Yes ‒2.60±0.00 ‒2.50±0.00 ‒2.60±0.00 ‒1.20±0.00
Health behavior Smoking No ‒2.40±1.01 0.243 0.808 ‒1.20±1.44 0.104 0.918 ‒1.83±0.99 0.731 0.467 ‒1.21±0.96 0.634 0.528
Yes ‒2.30±0.92 ‒2.02±1.25 ‒1.52±0.93 ‒0.95±0.88
Alcohol No ‒2.42±1.00 0.968 0.336 ‒1.99±1.43 0.921 0.360 ‒1.83±0.99 0.989 0.326 ‒1.21±0.97 0.834 0.407
Yes ‒1.93±0.92 ‒1.33±0.75 ‒1.33±0.75 ‒0.80±0.54
Body mass index Normal (a) ‒2.91±0.97 3.621 0.017 (a<b) ‒2.50±1.54 2.498 0.067 ‒2.25±0.87 2.441 0.072 ‒1.66±0.76 2.932 0.039
Overweight (b) ‒1.92±1.21 ‒1.48±1.44 ‒1.56±1.22 ‒1.05±1.14
Obese (c) ‒2.35±0.75 ‒1.98±1.01 ‒1.69±0.88 ‒1.02±0.90
Severely obese (d) ‒2.13±0.96 ‒0.93±2.47 ‒1.28±0.69 ‒0.58±0.62
Previous fracture history No ‒2.37±0.97 0.431 0.668 ‒1.95±1.43 0.141 0.888 ‒1.77±0.99 0.599 0.551 ‒1.14±0.97 0.957 0.342
Yes ‒2.50±1.14 ‒2.01±1.38 ‒1.94±0.99 ‒1.41±0.86

The BMD value presented corresponds to the lowest T-score among the measured sites. F value for analysis of variance among three or more groups.

Post-hoc; Scheffe, P<0.05

SD, standard deviation; t/F, test statistic (t value for two group comparisons).

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        Correlation of bone mineral density with ankle fractures in older adults in Korea: a retrospective cohort study
        J Musculoskelet Trauma. 2025;38(4):186-192.   Published online October 24, 2025
        DOI: https://doi.org/10.12671/jmt.2025.00150
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      Correlation of bone mineral density with ankle fractures in older adults in Korea: a retrospective cohort study
      Correlation of bone mineral density with ankle fractures in older adults in Korea: a retrospective cohort study
      Variable Value
      Age (yr) 71.64±5.74
       ≤69 31 (42.5)
       70‒79 33 (45.2)
       ≥80 9 (12.3)
      Sex (male:female) 28 (38.4):45 (61.6)
      Injury mechanism
       Twisting injury 28 (38.4)
       Slip down 40 (54.8)
       Fall down 3 (4.1)
       Other 2 (2.7)
      Comorbidity (no:yes)
       Diabetes 46 (63):27 (37)
       Hypertension 35 (47.9):38 (52.1)
       Dementia 72 (98.6):1 (1.4)
      Bone mineral density
       Normal 7 (9.7)
       Osteopenia 27 (37)
       Osteoporosis 39 (53.4)
      Health behavior (no:yes)
       Smoking 67 (91.8):6 (8.2)
       Alcohol 69 (94.5):4 (5.5)
      Body mass index (kg/m²) 24.89±3.16
       Normal 21 (28.8)
       Overweight 17 (23.3)
       Obese 31 (42.5)
       Severely obese 4 (5.5)
      Previous fracture history (no:yes) 59 (80.8):14 (19.2)
      Variable Category BMD
      		 Spine T-score
      		 Hip neck T-score
      		 Total hip T-score
      Mean±SD t/F P-value Mean±SD t/F P-value Mean±SD t/F P-value Mean±SD t/F P-value
      Total ‒2.40±1.00 ‒1.96±1.41 ‒1.80±0.99 ‒1.19±0.95
      Age (yr) ≤69a ‒2.09±0.84 3.967 0.023 (a>b) ‒1.62±1.24 3.697 0.03 (a>b) ‒1.55±0.98 4.508 0.014 (a>c) ‒0.92±0.93 5.015 0.009 (a>c)
      70‒79b ‒2.56±1.08 ‒2.36±1.29 ‒1.82±1.00 ‒1.26±0.95
      ≥80c ‒2.87±0.97 ‒1.66±2.08 ‒2.58±0.45 ‒1.87±0.71
      Sex Male ‒2.09±0.92 2.088 0.040 ‒1.53±1.51 2.117 0.038 ‒1.59±0.98 1.474 0.145 ‒0.87±1.00 2.299 0.024
      Female ‒2.58±1.01 ‒2.23±1.30 ‒1.93±0.98 ‒1.38±0.88
      Injury mechanism Twisting injury ‒2.38±0.80 2.003 0.122 ‒2.12±1.25 1.871 0.143 ‒1.63±0.96 1.279 0.288 ‒1.04±0.85 0.980 0.407
      Slip down ‒2.28±1.06 ‒1.69±1.44 ‒1.82±1.02 ‒1.22±1.02
      Fall down ‒3.40±0.56 ‒3.37±0.60 ‒2.53±0.32 ‒1.80±0.30
      Other ‒3.45±2.19 ‒2.80±3.11 ‒2.60±0.99 ‒1.85±1.63
      Comorbidity Diabetes No ‒2.55±1.02 1.793 0.077 ‒2.13±1.53 1.343 0.184 ‒1.84±1.04 0.317 0.752 ‒1.25±1.01 0.675 0.502
      Yes ‒2.13±0.93 ‒1.67±1.16 ‒1.75±0.90 ‒1.09±0.86
      Hypertension No ‒2.37±1.11 0.176 0.861 ‒2.11±1.35 0.883 0.380 ‒1.63±1.14 1.384 0.171 ‒1.03±1.09 1.376 0.173
      Yes ‒2.42±0.90 ‒1.82±1.48 ‒1.95±0.81 ‒1.33±0.79
      Dementia No ‒2.39±1.01 0.204 0.839 ‒1.95±1.42 0.383 0.703 ‒1.79±0.99 0.814 0.419 ‒1.19±0.96 0.013 0.99
      Yes ‒2.60±0.00 ‒2.50±0.00 ‒2.60±0.00 ‒1.20±0.00
      Health behavior Smoking No ‒2.40±1.01 0.243 0.808 ‒1.20±1.44 0.104 0.918 ‒1.83±0.99 0.731 0.467 ‒1.21±0.96 0.634 0.528
      Yes ‒2.30±0.92 ‒2.02±1.25 ‒1.52±0.93 ‒0.95±0.88
      Alcohol No ‒2.42±1.00 0.968 0.336 ‒1.99±1.43 0.921 0.360 ‒1.83±0.99 0.989 0.326 ‒1.21±0.97 0.834 0.407
      Yes ‒1.93±0.92 ‒1.33±0.75 ‒1.33±0.75 ‒0.80±0.54
      Body mass index Normal (a) ‒2.91±0.97 3.621 0.017 (a<b) ‒2.50±1.54 2.498 0.067 ‒2.25±0.87 2.441 0.072 ‒1.66±0.76 2.932 0.039
      Overweight (b) ‒1.92±1.21 ‒1.48±1.44 ‒1.56±1.22 ‒1.05±1.14
      Obese (c) ‒2.35±0.75 ‒1.98±1.01 ‒1.69±0.88 ‒1.02±0.90
      Severely obese (d) ‒2.13±0.96 ‒0.93±2.47 ‒1.28±0.69 ‒0.58±0.62
      Previous fracture history No ‒2.37±0.97 0.431 0.668 ‒1.95±1.43 0.141 0.888 ‒1.77±0.99 0.599 0.551 ‒1.14±0.97 0.957 0.342
      Yes ‒2.50±1.14 ‒2.01±1.38 ‒1.94±0.99 ‒1.41±0.86
      Table 1. Demographics of the patients (n=73)

      Values are presented as mean±standard deviation or number (%).

      Table 2. Associations between bone mineral density (BMD) and patients’ characteristics (n=73)

      The BMD value presented corresponds to the lowest T-score among the measured sites. F value for analysis of variance among three or more groups.

      Post-hoc; Scheffe, P<0.05

      SD, standard deviation; t/F, test statistic (t value for two group comparisons).

      Table 1.

      Table 2.

      J Musculoskelet Trauma : Journal of Musculoskeletal Trauma
      © The Korean Orthopaedic Trauma Association.
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