A Study on Osteoporosis Status and Related Risk Factors Among Elderly Patients at the Hospital for Traumatology and Orthopedics from 2023 to 2025: A Cross-Sectional Study in Vietnam

1. Introduction

Worldwide, more than 200 million people are estimated to be affected by osteoporosis [1]. In 2010, it was estimated that 27.5 million people had osteoporosis in five countries, including Germany, Italy, France, England and Spain [2]. In the United States, statistics indicate that more than 10 million individuals are affected by osteoporosis, while an additional up to 47 million have low bone density [3]. Osteoporosis arises from disrupted bone remodeling characterized by excessive bone resorption relative to bone formation [4]. Osteoporosis is classified into two types based on its cause: primary and secondary [5]. Primary osteoporosis is usually asymptomatic and often remains undetected until bone density loss is significant [6].

In adults, bone resorption and bone formation occur in balance. Following the attainment of peak bone mass, bone mass progressively declines with advancing age, although the rate of decline varies among individuals. Since estrogen and testosterone play essential roles in bone formation, changes in the levels of can significantly influence bone loss [7,8]. Accordingly, there are significant differences between men and women in the timing of osteoporosis onset. The risk factors of osteoporosis are highly diverse, including a calcium-deficient diet, poor nutrition, age, gender and irregular physical activity, making its prevention particularly challenging [9,10,11]. Therefore, the prevention of osteoporosis remains a major challenge for healthcare systems.

One of the most serious complications of osteoporosis is osteoporotic fracture. It is estimated that there are 37 million osteoporotic fractures worldwide each year among patients who are over 55, with three osteoporotic fractures occurring every three seconds [12]. The number of hip fractures is projected to increase from roughly 1.7 million in 1990 to 6.3 million by 2050, with the most substantial rise expected in Asia [13]. Osteoporotic fractures often result in chronic pain and disability, leading to increased dependence on care and higher mortality rates among affected individuals [14,15]. Due to increased life expectancy and socioeconomic development, osteoporosis has become a common health problem associated with substantial healthcare costs. It is predicted that by 2050, around 2.5 million cases of hip fractures will occur in Asia [16]. In the United Kingdom, the total cost of treating osteoporotic fractures accounted for approximately 2.4% of healthcare expenditure (equivalent to £5.4 billion) in 2019 [17].

In Vietnam, the prevalence of osteoporosis in women aged 50 years and older is 24.6%, which is 1.7 times higher than that in men. The rate of population aging is occurring rapidly and no elderly care models was implemented due to regional and cultural characteristics [18]. That is one of the factors contributing to the increasing prevalence of osteoporosis, causing many negative impacts on public health. Beyond their detrimental effects on quality of life, osteoporotic fractures impose substantial healthcare, economic, and social burdens on families and the broader society. Some studies on the Vietnamese population focus on postmenopausal women and men who are over 50 years old. It indicated that approximately one-third of women and one in ten men are at high risk of fracture [19]. However, the research using dual energy X-ray absorptiometry (DEXA) on both the lumbar spine and femoral neck is still limited. Furthermore, no research in Vietnam has characterized postmenopausal duration as a graded risk factor. To gain a deeper understanding of osteoporosis and the risk factors in Vietnam, this study was conducted to: (1) describe the prevalence of osteoporosis and (2) analyze several risk factors among elderly patients.

2. Materials and Methods

2.1. Data Collection and Participants Characteristics

The dataset was collected from the elderly patients who attended the Rheumatology Department of the Hospital for Traumatology and Orthopaedics from 2023 to 2025. The total of 400 patients was chose by the sample size equation.

Including criteria:

The patients who are:

• Above 60 years old.
• Able to ambulate independently.
• Agree to undergo all required paraclinical/laboratory investigations.
• Independently complete the interview questionnaire.
• Willingness to participate throughout the entire study period.

Exclusion criteria:

• Patients with psychiatric disorders, dementia, or cognitive impairment.
• Patients with a history or current diagnosis of bone diseases, including hyperparathyroidism, hypoparathyroidism, Paget’s disease, osteomalacia, renal osteodystrophy, osteogenesis imperfecta, bone metastases from cancer, evidence of renal failure, or a history of oophorectomy.
• Patients with a history of hip replacement or bilateral femoral neck fracture.
• Patients who are unable to move for BMD measurement.
• Patients for whom BMD measurement at the lumbar spine or femoral neck cannot be performed due to femoral head replacement, bilateral femoral neck fractures, or prior lumbar spine surgery.

Sample size

$$n=Z_{\left(1-{\displaystyle \frac{\alpha }{2}}\right)}^{2}x{\displaystyle \frac{p\left(1-p\right)}{d^2}}$$

Where:

n: minimum sample size required for the study.

p: the estimated prevalence of osteoporosis among elderly patients visiting the Rheumatology Clinic at the Orthopedic and Trauma Hospital during the period 2023–2025. In this study, p = 0.5 was used because no previous study had been conducted at this hospital; this value also ensures the maximum sample size.

Z: the standard normal deviate corresponding to a 95% confidence level ( α= 0.05), where Z = 1.96.

d: the acceptable margin of error; in this study d = 0.05 was used.

Substituting these parameters into the formula yielded a minimum required sample size of 385 older participants.

Sampling method

Patients aged 60 years and older who visited the Rheumatology Clinic of the Hospital for Traumatology and Orthopedics and met the study inclusion criteria were recruited consecutively from October 2023 to March 2025, or until the required sample size was achieved.

2.2. Study Designs

A cross-sectional study was conducted. The structured questionnaire was designed some basic information such as general demographics, lifestyle habits and clinical characteristics. The general demographics comprises age, gender, occupational activity level. The clinical characteristics includes the medical records: history of fractures, postmenopausal record

Measurements

Body Max Index criteria

The Body Max Index (BMI) is calculated as this formula:

$$BMI={\displaystyle \frac{weight\left(kg\right)}{{height}^2\left(m^2\right)}}$$

The BMI status was categorized according to the World Health Organization (WHO) Asia-Pacific regional criteria (2004), applying to both genders:

• BMI < 18.5 kg/m² : Underweight
• 18.5 ≤ BMI < 23.0 kg/m²: Normal weight
• 23.0 ≤ BMI < 25 kg/m²: Overweight
• BMI ≥ 25 kg/m²: Obesity

Bone Mineral Density (BMD) measurements

DEXA is based on the principle of differential X-ray attenuation, which enables the quantification of bone mineral mass distinct from surrounding soft tissue. In this study, BMD was measured at the lumbar spine (L1–L4) and femoral neck. The bone mineral density was described by T-score, reported in standard deviation (SD) units.

Bone Mineral Density (BMD) criteria

The BMD was evaluated according to the WHO diagnostic criteria base on the T-score:

• T-score ≥ 1: Normal
• −2.5 < T-score < 1: Osteopenia
• T-score ≤ 2.5: Osteoporosis
• T-score ≤ 2.5 and fragility fracture: Severe osteoporosis

2.3. Statistics Analysis

The data was analyzed by R version 4.6.0 (R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/). The ratio observation is compared by Chi-squared test. Fisher’s exact test was used to compare proportions when the expected cell frequency was less than 5. Descriptive statistics, including mean values, standard deviations and percentages, were calculated.

Additionally, a multivariable logistic regression model was performed to evaluate the correlation between variables. The target outcome variable is binary, include non-osteoporosis (0) and osteoporosis (1). The model simultaneously includes the age, BMI value that was treated as a continuous variable and the history of fracture is also a categorical variable (“No” is the reference group):

logit(P(Y = 1)) = β₀ + β₁ (Age) + β₂ (BMI group) + β₃ (History of fracture _Yes) + β₄ (History of fracture _Unknown)

3. Results

3.1. Baseline Characteristics of Participants

This study was conducted on a total of 400 patients, the majority of whom were female. The number of female patients was 7.89 times higher than that of males. The mean age of the study population was 66.88 ± 6.45, ranging from 60 to 96 years (Table 1).

In this study, the 60-69 age group was the most prevalent, accounting for 70.5% of the cohort, followed by the 70–79 age group at 25.5% and those aged 80 years or older at 4.0%. The prevalence of bone mineral density abnormalities differed significantly across anatomical sites: The prevalence of osteoporosis at the lumbar spine (29.75%) was higher than that at the femoral neck (6%). At the lumbar spine, it was observed a progressive increase in the prevalence of osteoporosis with advancing age. Specifically, the rates were 29.1% in the 60–69 age group, 28.4% in the 70–79 age group, and 50.0% in those aged 80 years or older. However, this baseline trend did not reach statistical significance (p > 0.05). On the other hand, at femoral neck, the prevalence of osteoporosis rose dramatically with age. The rates were 5.0% in the 60-69 group, 5.9% in the 70-70 group and 25.0% in the patients aged 80 or older. This difference was statistically significant across all three age cohorts (p <0.05) (Figure 1).

3.2. Risk Factors of Osteoporosis

3.2.1. Sex, BMI and Physical Activity

At the lumbar spine, both BMI and sex are significantly associated with bone density. The prevalence of osteoporosis in females (95.8%) was significantly higher than in males (4.2%), and this difference was statistically significant (p < 0.05); the patients with a BMI < 23 account for 51.26% of the osteoporosis group, compared to only 31.09% in the normal group. However, at the femoral neck, the prevalence of osteoporosis was not recorded in males, while 24 cases were recorded in females (p > 0.05). In addition, with the patients whose BMI > 23, it was demonstrated that the osteoporosis rate is lower than the group with BMI < 23 (p < 0.05) at lumbar spine and femoral neck. Regarding the physical activity factor, it was observed the high ratio of osteoporosis in patients who have less activity, rather than active group, but this difference was not statistically significant (p > 0.05) at either the lumbar spine or the femoral neck (Table 1).

3.2.2. Postmenopausal Period and Osteoporosis

It was observed that the duration of time elapsed since menopause is a critical factor of bone density. At the lumbar spine, the prevalence of osteoporosis increases continuously across all categories. Patients less than 10 years postmenopause demonstrate a 21.0% prevalence, which more than triples to 61.5% in patients who are 30 or more years postmenopause. Similar to the lumbar spine, at the femoral neck, it was shown the onset of osteoporosis appears lagged. The prevalence of osteoporosis remains low initially for < 10 years, then rising to 3.8% in the 10-19 years group and finally, increase dramatically to 19.2% after ≥ 30 years postmenopause (Figure 2). This relationship is confirmed by Chi-square test with p-value < 0.05 at both anatomy sites.

3.2.3. History of Fracture and Osteoporosis Status

The association between a history of fracture and bone mineral density status at the lumbar spine and femoral neck was analyzed (Table 2). At the lumbar spine, a history of fracture was significantly associated with bone status (p < 0.05). Among the participants, those with a history of fracture accounted for 28.57% of the non-osteoporosis group, 57.14% had no history of fracture, and 14.29% had an unknown status, compared to 16.73%, 68.33%, and 14.95% in the non-osteoporosis group, respectively.

Similarly, a statistically significant association was observed at the femoral neck (p < 0.05, Fisher's exact test). In this region, individuals with a history of fracture accounted for 45.83% of the osteoporosis group compared to only 18.62% of the non-osteoporosis group. Conversely, those without a fracture history represented 54.17% and 65.69% of the osteoporosis and non-osteoporosis groups, respectively, while an unknown fracture status accounted for 0.00% and 15.69%.

3.3. A Multivariable Logistic Regression

To evaluate the independent factors associated with osteoporosis at the lumbar spine, a multivariable logistic regression analysis was conducted. In this regression model (N = 400), history of fracture and BMI were significantly associated with osteoporosis at the lumbar spine. Specifically, patients with a history of fracture had 86% higher odds of having osteoporosis compared to those without fracture history (adjusted OR = 1.86, 95% CI: 1.09 - 3.17, p = 0.022). Conversely, higher BMI served as an independent protective factor, with each unit increase in BMI associated with an 11% reduction in the odds of osteoporosis (adjusted OR = 0.89, 95% CI: 0.83 - 0.95, p < 0.001). No statistically significant association was observed for age (aOR = 1.01, p = 0.455) or the unknown fracture status category (aOR = 1.08, p = 0.815) (Figure 3, Table 3).

4. Discussion

The mean age of the patients was 66.88 ± 6.5 years. The most predominant age group was 60–69 years, accounting for 70.5% of the study population, followed by 70–79 years (25.5%) and age 80 years (4.0%). The percentage of female participants is significantly higher than that of male participants. This number partly reflects broader community trends, where females are more likely to undergo screening and follow-up care than males [20,21].

The study showed that the percentage of osteoporosis inthe lumbar spine is higher than that in the femoral neck. This result is consistent with the literature: the lumbar spine, comprising the L1–L4 vertebrae, consists predominantly of trabecular bone [22]. The trabecular bone exhibits a greater rate of annual bone loss compared to cortical bone due to its higher metabolic turnover, thereby accounting for the earlier manifestation of osteoporosis in the lumbar spine relative to the femoral neck [23]. The BMD was associated with both sex and BMI. Females constituted the vast majority of patients in the osteoporosis group compared to males. Furthermore, the patients with low BMI represented a higher proportion of the osteoporosis group than the normal bone density group. The time elapsed since menopause was identified as an important determinant of BMD. At the lumbar spine, the prevalence of osteoporosis increased progressively with increasing years since menopause. A similar pattern was observed at the femoral neck, although the increase appeared to occur at a later stage. The association between years since menopause and osteoporosis prevalence was statistically significant at both anatomical sites, as demonstrated by the chi-square test (p < 0.05). At the lumbar spine, fracture history was significantly associated with bone status. Among participants with osteoporosis, 28.57% had a history of fracture, 57.14% had no history of fracture, and 14.29% had an unknown fracture status. The same association was observed at the femoral neck, where 45.83% of participants with osteoporosis had a history of fracture, compared with 18.62% of those without osteoporosis.

This study still has some limitations, such as the relatively short timeline, the number of male participations and the data remain susceptible to recall bias, which is inherently common among elderly cohorts. The disparity in the male-to-female ratio constitutes a notable limitation.

5. Conclusions

Osteoporosis is a crucial public health concern among elderly adults and a leading cause of fragility fractures. It affects quality of life, reduces life expectancy and places considerable financial pressure on healthcare systems globally. Consequently, early identification of risk factors, prompt diagnosis and appropriate therapeutic intervention are paramount to mitigating fracture incidence and optimizing patient outcomes. The findings of this study underscore that targeted osteoporosis screening among high-risk patient populations can facilitate early detection and guide prophylactic strategies to prevent fractures. Crucially, many lower-tier hospitals lack DEXA equipment, so healthcare providers should maintain high clinical vigilance for osteoporotic vertebral fractures and expedite spinal imaging to establish a definitive diagnosis. Therefore, enhancing osteoporosis surveys in the older population is necessary, especially among postmenopausal women and all individuals older than 50 years.