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Top comorbidities in osteoporotic fracture patients in a northeast population in China

樱花视频 volume听25, Article听number:听1640 (2025) Cite this article

Abstract

Background

Osteoporotic fractures frequently occur in conjunction with various diseases, and the comorbidity of fractures is a significant contributor to their high disability and mortality rates. This study aimed to examine the pattern of comorbidity in fracture patients and non-fracture individuals.

Methods

Using data from community- and hospital-based populations in Jilin, China, we identified osteoporotic fracture patients over 40 years of age. We matched each fracture patient with two non-fracture individuals based on age (卤鈥�3 years) and sex. Major comorbidities including hypertension, type 2 diabetes, hyperlipidemia, obesity, coronary heart disease (CHD), stroke, hyperthyroidism, hyperparathyroidism, osteoporosis, rheumatoid arthritis, respiratory diseases, gastrointestinal diseases, and breast cancer, were ascrertained from patients鈥� laboratory test results and self-reported data.

Results

We identified 51 hospital-based fracture patients, 181 community-based fracture patients and 362 matched non-fracture individuals. The mean age for both overall fracture patients and non-fracture individuals was 67.8 years. Females accounted for 72.8% of overall fracture patients and 71.8% of non-fracture individuals. The most common comorbidity was hypertension for overall fracture patients (45.3%), hospital-based fracture patients (39.2%), and non-fracture individuals (56.4%), whereas hyperlipidemia was the most frequent condition for community-based fracture patients (63.6%). The top binary comorbidity combination pattern for community-based fracture patients (30.4%) and non-fracture individuals (29.6%) was hyperlipidemia & hypertension, while for hospital-based (15.7%) and overall (15.1%) fracture patients it was hypertension & type 2 diabetes. The average degree of comorbidity network for overall fracture patients (7.0) was higher than that for non-fracture individuals (5.4).

Conclusions

The most common comorbidities were hyperlipidemia and hypertension among fracture patients. As compared to non-fracture individuals, fracture patients exhibited a more complex comorbidity network. These findings help us better target the management of comorbidities in patients with osteoporotic fractures and reduce the burden associated with fractures.

Trial registration

Not applicable.

Peer Review reports

Introduction

Osteoporotic fractures have become a major public health issue in China. It is expected that more than one third of Chinese women and approximately one tenth of Chinese men aged 50 years or older will have an osteoporotic fracture at one time point in the future [1]. It is projected that the cost of osteoporotic fractures in China during 2035 will be double that of 2010, reaching $18.9听billion; by 2050, the costs will nearly be $25.45听billion [1]. The excess mortality rate of patients with hip fractures in China is approximately nine times higher than that of the general population [2].

Approximately 55鈥�98% of older adults are affected by two or more chronic conditions [3]. The prevalence of comorbidity increases with age, with projections of 13.1% by the year 2050 [4]. Comorbidities are closely associated with greater rates of hospitalization [5] and psychological distress [6]. A study has shown that comorbidities use much higher health expenditure than a single chronic condition [7]. Comorbidities elevate the risk of mortality, with each additional chronic disease further exacerbating mortality risk [8].

Most patients with osteoporotic fractures suffer from multiple comorbidities, such as hypertension, diabetes, stroke, rheumatoid arthritis, and hyperthyroidism [9]. Previous studies have shown that excess mortality following an osteoporotic fracture is largely due to comorbidities [10, 11]. For instance, cardiovascular disease (CVD) increases the risk of death in fracture patients by 3 to 4 times [12]. Mortality risk was 13 times higher among individuals who experienced a stroke than those without the disease following an osteoporotic vertebral fracture [13]. Patients with type 2 diabetes had a 44% increased post-fracture mortality compared to non-diabetics [14].

Due to the serious threat of comorbidities to the lives of patients with osteoporotic fractures, it is important to examine osteoporotic fracture associated comorbidities. Nevertheless, the majority of fracture-morbidity studies focused on the relationship between fractures and a single chronic disease, lacking the exploration of top comorbidities associated with fractures. Existing studies have found the independent relationship of osteoporotic fractures with hypertension, diabetes, and stroke [15]. Furthermore, the ranking of comorbidities associated with osteoporotic fractures is inconsistent. For example, an Israeli study showed that the top three comorbidities of vertebral fracture patients are hypertension, ischemic heart disease, and diabetes [16]. In comparison, hypertension is the most prevalent comorbidity in hip fracture patients in China, followed by anemia, and diabetes [17]. In a Danish study, however, CVD, cancer, and hypertension were observed as three of the most common comorbidities associated with fractures [18]. Therefore, we examined the top comorbidities among prevalent and recent osteoporotic fracture patients and non-fracture individuals among a northeastern population in China. Understanding the patterns of comorbidities associated with fractures is essential for developing patient-oriented treatment and care strategies. This study may help to control the osteoporotic fracture related burdens, including mortality.

Methods

Study setting and population

In this study, the data of osteoporotic fracture participants were derived from two sources: (1) a cross-sectional survey of a community-based population in Changchun, Jilin, China in 2019, which was a part of the Comprehensive Demonstration Research Project of Major Chronic Noncommunicable Disease Prevention and Control Technology in Northeast China organized by the China Medical University [19]; and (2) from the electronic medical records (EMRs) and questionnaires of recent osteoporotic fracture inpatients (time between interview and fracture diagnosis was within 2 days) within the Second Hospital of Jilin University (Jilin, China) from 2019 to 2020, which is a major diagnosis and treatment center for treating severe diseases (i.e., cancers, cardiovascular diseases, and osteoporosis) in northeast China. The questionnaires for community-based population and hospital-based fracture patients are shown in Table S1.

In the community-based population, we identified patients aged 40 years or older with self-reported osteoporotic fractures. Individuals were excluded if they (a) had incomplete data about comorbidities, or (b) had missing data on demographic characteristics (i.e., age and sex). Using the same population and exclusion criteria, we matched each community-based fracture patient with two non-fracture individuals based on age (卤鈥�3 years) and sex. In the hospital-based population, we included patients aged 40 years or older who were diagnosed with recent osteoporotic fractures by X-ray. Individuals were excluded using the same criteria as above. All fractures in the community- and hospital-based populations that occurred due to high trauma (e.g., car accidents and/or fall above standing height) were excluded. The ethics committee of China Medical University and the institutional review board (IRB) of The Second Hospital of Jilin University approved this study (Approval #: 2019-01-30). All patients provided written informed consent before data collection.

Osteoporotic fracture ascertainment and classification

In the community-based population, self-reported data on osteoporotic fracture diagnosed by a hospital at the county level or above, including hip, distal forearm, vertebral, proximal humerus, pelvis, ankle, and other fractures, were collected. In the hospital-based population, all skeletal sites of the osteoporotic fractures previously described were diagnosed by X-ray. We classified these fractures into three groups: hip, distal forearm, and other fractures.

Comorbidity ascertainment

We included 13 chronic diseases identified based on previous studies [20, 21]: hypertension, type 2 diabetes, hyperlipidemia, obesity, coronary heart disease (CHD), stroke, hyperthyroidism, hyperparathyroidism, osteoporosis, rheumatoid arthritis, respiratory diseases (including asthma, chronic bronchitis, emphysema, chronic obstructive pulmonary disease and lung cancer), gastrointestinal diseases (including chronic gastrointestinal diseases, gastric cancer and colorectal cancer) and breast cancer (only in females). While we considered other conditions (e.g., epilepsy, Parkinson disease, osteogenesis imperfect, chronic malnutrition and chronic liver diseases), they were not included as the frequency of these conditions was zero in our study population. According to the Chinese guideline [20], hyperlipidemia was defined as having a total cholesterol (TC)鈥夆墺鈥�6.2 mmol/L, triglycerides (TG)鈥夆墺鈥�2.3 mmol/L, high-density lipoprotein (HDL-C)鈥�<鈥�1.0 mmol/L, or low-density lipoprotein (LDL-C)鈥夆墺鈥�4.1 mmol/L. Individuals who used antihyperlipidemic medications or had self-reported a history of hyperlipidemia were also considered to have hyperlipidemia. Hypertension was defined as a blood pressure 鈮� 140/90 mmHg, or if an individual used antihypertensive drugs or had a self-reported history of hypertension [21]. We excluded individuals who had self-reported hypertension, but had a measured blood pressure that was considered normal while not using antihypertensive medications. We defined type 2 diabetes based on fasting plasma glucose (FPG) 鈮� 7.0 mmol/L or a self-reported history of the disease [22]. Body weight and height were measured in the community-based population and self-reported in the hospital-based population. Body mass index (BMI) was calculated as weight (kg) divided by the square of height (m). Body mass index (BMI) values 鈮� 28听kg/m2 were considered as obese [23]. Other comorbidities were self-reported diseases that were diagnosed in hospitals at the county level and above. These self-reported comorbidities were not validated.

Demographic characteristic ascertainment

Demographic characteristics included age, sex, ethnicity, marital status, retirement status, smoking, and alcohol consumption. Smoking status was categorized as non-smokers and smokers. Non-smokers were defined as those who nevered smoked. Current and/or past smokers were considered as smokers. Alcohol consumption status was defined using two categories: non-drinkers and drinkers. Those who did not drink at all were classified as non-drinkers. Current and/or past drinkers were divided into drinkers.

Statistical analysis

We descriptively analyzed the characteristics of fracture patients and non-fracture individuals. We tested the prevalence of comorbidities among fracture patients and non-fracture individuals. Stratified analyses by population sources, sex, age, and fracture sites were also performed. Because there were missing data on skeletal sites for some community-based fractures, subgroup analysis by fracture site was only conducted among those with complete fracture site information. The prevalence of comorbidities was compared by 蠂2 test or conditional logistic regression (for matched data). The Fisher鈥檚 exact test was used when the expected frequency was below five. We also analyzed the frequency of comorbidity patterns in binary and ternary combinations.

Comorbidity network was used to visualize the association between comorbidities. The nodes of the network indicate diseases and the height of each node is proportional to the prevalence of each disease. An edge in the network represents the co-occurrence of two diseases connected by the edge. The weight of an edge is proportional to the number of co-occurrences of those two diseases. When a subject has more than two comorbidities, aside from osteoporotic fractures, the count of each comorbidity pair has an increment of one. For example, when an individual with an osteoporotic fracture additionally has comorbidities A, B and C, then the comorbidity pairs A-B, A-C, and B-C will have an increment of one. The comorbidities with a prevalence higher than 1% are listed in the networks in our study. Two indicators, degree centrality and average degree, were used to evaluate the comorbidity network. Degree centrality refers to the number of nodes that a node is connected to, which measures the participation of the node in the network. The higher the degree centrality of a node, the more ties it has with other nodes in the network [24]. Average degree is an indicator to measure the sparsity of the network. Average degree is the average value of the number of connected nodes. The higher the average degree, the higher connection the degree has among nodes in the network, and the denser the network [25]. In this study, a higher average degree of the comorbidity network indicates that the connections between comorbidities in the population are more complex.

Due to the lack of data on hyperlipidemia in the hospital-based fracture patients, we only considered hyperlipidemia data in the community-based population. Two-sided P鈥�< 0.05 was considered to be statistically significant. All analyses were performed using the SPSS version 24.0 (IBM, Inc., NY, USA) and R version 4.3.1 (R Foundation for Statistical Computing, Vienna, Austria). The visualization of comorbidity networks was conducted by the Cytoscape version 3.10.0 (Cytoscape Consortium, San Diego, CA, USA).

Results

Patient characteristics

This study identified 51 hospital-based fracture patients, 181 community-based fracture patients and 362 matched non-fracture individuals (Table听1). The mean age for both the overall fracture patients and non-fracture individuals was 67.8 years. Females accounted for 72.8% of the overall fracture patients and 71.8% of non-fracture individuals. The majority of fracture patients and non-fracture individuals were ethnically of Han descent, retirees, or married/cohabitation. Other characteristics were not significally different between community- and hospital-based fracture patients, between community-based fracture patients and non-fracture individuals, or between the overall fracture patients and non-fracture individuals (all P鈥�&驳迟;鈥�0.05).

Table 1 Characteristics of fracture patients and non-fracture individuals
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Comorbidity prevalence

Table听2 presents the comorbidities of fracture patients and non-fracture individuals. Overall, the most common comorbidity among the community-based fracture patients was hyperlipidemia (63.6%), followed by hypertension (47.0%), and type 2 diabetes (24.9%). Aside from hyperlipidemia, hypertension was the most common condition among the hospital-based (39.2%) and overall (45.3%) fracture patients. Hypertension was the top comorbidity among non-fracture individuals (56.4%). Similar results were noted after stratifying by sex, age, and fracture site, though type 2 diabetes was slightly more common than hypertension among hip fracture patients (Tables S2, S3, S4).

Table 2 Comorbidities of fracture patients and non-fracture individuals
Full size table

Table听3 lists the top five binary comorbidity combinations among fracture patients and non-fracture individuals. Hyperlipidemia & hypertension was the top comorbidity combination pattern for the community-based fracture patients (30.4%) and non-fracture individuals (29.6%). However, hypertension & type 2 diabetes was the most common comorbidity combination for the hospital-based (15.7%) and overall (15.1%) fracture patients.

Table 3 Top five binary comorbidity combinations of fracture patients and non-fracture individuals
Full size table

Table听4 displays the top five ternary comorbidity combinations of fracture patients and non-fracture individuals. Overall, the top ternary comorbidity combination for overall fracture patients was hypertension & type 2 diabetes & CHD (4.7%). Differing top ternary comorbidity combinations were found for community- (hyperlipidemia & hypertension & obesity; 11.0%) and hospital-based (hypertension & type 2 diabetes & stroke, and hypertension & type 2 diabetes & CHD; both prevalence ternary combinations was 7.8%) fracture patients and non-fracture individuals (hyperlipidemia & hypertension & type 2 diabetes; 9.9%).

Table 4 Top five ternary comorbidity combinations of fracture patients and non-fracture individuals
Full size table

Comorbidity network

Figure听1 shows the comorbidity network among fracture patients and non-fracture individuals. Among overall fracture patients, hypertension had the highest degree centrality. The degree centrality of comorbidities was slightly different for the community- (hyperlipidemia and hypertension) and hospital-based (hypertension and osteoporosis) fracture patients. The average degree of comorbidity network was 7.0 among overall fracture patients, 7.5 among community-based fracture patients, and 6.0 among hospital-based fracture patients. The average degree of comorbidity network in non-fracture individuals was 5.4.

Fig. 1
figure 1

Comorbidity network among (a) overall fracture patients; (b) community-based fracture patients; (c) hospital-based fracture patients; (d) non-fracture individuals. CHD: coronary heart disease; Gastrointestinal: gastrointestinal diseases; Respiratory: respiratory diseases; Rheumatoid: rheumatoid arthritis

Full size image

Discussion

In this cross-sectional study in northeast China, we found that the top three comorbidities for fracture patients and non-fracture individuals were hyperlipidemia, hypertension, and type 2 diabetes. Aside from the missing data on hyperlipidemia among hospital-based and overall fracture patients, these comorbidities had little differences across sex, age, and fracture site. The dominant binary comorbidity combination pattern was hyperlipidemia & hypertension among community-based fracture patients and non-fracture individuals, and hypertension & type 2 diabetes for hospital-based and overall fracture patients. The top ternary comorbidity combination patterns varied between the overall (hypertension & type 2 diabetes & CHD), community- (hyperlipidemia & hypertension & obesity), hospital-based (hypertension & type 2 diabetes & stroke, and hypertension & type 2 diabetes & CHD) fracture patients and non-fracture individuals (hyperlipidemia & hypertension & type 2 diabetes). The average degree of comorbidity network for fracture patients was higher than that of non-fracture individuals.

We found that the top comorbidities for fracture patients and non-fracture individuals include hyperlipidemia, hypertension, and type 2 diabetes. This is partly consistent with a recent real-world analysis of 1823 fracture patients, among whom hyperlipidemia, hypertension and type 2 diabetes accounted for 45.9%, 38.2%, and 19.4% in males and 47.1%, 31.0%, and 21.5% in females, respectively [26]. These three conditions were also highly prevalent among community-based populations elsewhere [8, 27]. This partly supports our results among non-fracture individuals. Hypertension and type 2 diabetes are significantly associated with increased risk of fracture, though the underlying mechanisms remain underexplored [28, 29]. The Cardiovascular Health Study found that higher levels of lipids and lipoproteins are associated with higher hip fracture risk [30]. Whether hyperlipidemia is correlated with other fractures remain unclear.

In our study, osteoporosis was not so commonly presented among fracture patients. This may be due to the general low awareness of osteoporosis in China [31], and that most of the community have never received bone mineral density testing. Considering the significance of osteoporosis in fracture, it is recommended that osteoporosis screening be included in the routine elderly health checkup. We also found that patients with hip fractures were more likely to suffer from type 2 diabetes, hypertension, stroke, and osteoporosis. The probable cause of this phenomenon can be attributed to the shared risk factors between hip fractures and several chronic diseases. Other investigators have also noted this [32].

The primary binary comorbidity combination patterns of fracture patients were hyperlipidemia & hypertension as well as hypertension & type 2 diabetes. The major ternary comorbidity combination patterns were hyperlipidemia & hypertension & obesity, hypertension & type 2 diabetes & stroke, and hypertension & type 2 diabetes & CHD. Few studies have shown these results. However, this finding is partly supported by a previous Chinese comorbidity study, in which hypertension and hyperlipidemia, and their binary combination were major comorbidities [33].

Hypertension and hyperlipidemia had a comorbidity with the highest degree centrality in our study. Patients with these two diseases are therefore most likely to have a combination of other diseases. In parallel, hypertension and hyperlipidemia are closely related and are both risk factors for cardiovascular disease [34]. Both blood pressure and blood lipid levels should be actively controlled to prevent further complications. Combinations of hyperlipidemia, hypertension, obesity, and type 2 diabetes occurred most frequently among the community-based population. A previous study has reached a similar conclusion [27]. Obesity had a higher degree centrality among community-based fracture patients than among hospital-based fracture patients. Patients with obesity often suffer from various other diseases. Numerous studies have proven that obesity is a risk factor for hypertension, hyperlipidemia, type 2 diabetes, and many other diseases [35, 36]. Further network analysis indicated that the average degree of comorbidity network of fracture patients was higher than that of non-fracture individuals. This may help explain the higher mortality rate among fracture patients than that among non-fracture individuals [37].

We conducted stratified analyses for hospital- and community-based fracture cases, because fractures ascertained from these two populations are different from various perspectives. First, hospital-based fracture cases were ascertained based on x-ray, whereas the community-based fractures were self-reported. Second, hyperlipidemia data was only available among community-based fracture patients, but not among hospital-based fracture patients. Lastly, all hospital-based fractures were very recent (time between interview and fracture diagnosis was within 2 days). However, community-based fractures had no restrictions on the timing of the fracture prior to interview.

Osteoporotic fractures remain the major public health issue in China due to their high prevalence, financial burden, and excessive mortality [1, 2]. Comorbidities, such as hyperlipidemia, hypertension, and type 2 diabetes, and binary comorbidity combinations, such as hypertension & type 2 diabetes as well as hypertension & hyperlipidemia are very common among fracture patients. These findings are useful for developing patient-oriented management strategies to address comorbidities (i.e., hyperlipidemia, hypertension, and type 2 diabetes) in patients with osteoporotic fractures. This may also help to reduce the burden (i.e., mortality) associated with fractures.

Several limitations of this study should be mentioned. First, the data we analyzed were from a population in northeastern China, so the results may not reflect other regions of the country. Second, the small sample size may affect the precision of the estimates. Although we investigated a total of 8394 cases in a community-based population, the self-reported instances of fractures were relatively rare. Fractures in this population were mainly obtained through questionnaires, which may result in underreporting and subsequently an underestimation of the true number of fractures. Third, some comorbidities had a low frequency, which may have resulted in unstable estimates. Fourth, we did not have hyperlipidemia data for hospital-based fracture patients. Fifth, some comorbidities and the hospital-based data on body height and weight were self-reported, which could potentially result in misclassification due to reporting bias. Sixth, data for the hospital-based fracture patients were from self-reports and the EMRs, whereas data from the community-based fracture patients were mainly from self-reported data. We cannot fully exclude the possibility of bias from different data collection methods. Lastly, since this study was cross-sectional, the temporality and causality between osteoporotic fractures and comorbidities cannot be determined.

Conclusion

This study investigated the common comorbidities and comorbidity combination patterns in fracture patients and non-fracture individuals. Hyperlipidemia, hypertension, and type 2 diabetes are the major comorbidities among fracture patients. Hypertension & type 2 diabetes as well as hyperlipidemia & hypertension are the dominant binary comorbidity combinations for fracture patients. As compared to non-fracture individuals, patients with osteoporotic fractures exhibited a more complex comorbidity network. Our findings warrant further confirmation.

Data availability

The datasets generated and/or analyzed during the current study are not publicly available due to ethical reasons but are available from the corresponding author on reasonable request.

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Funding

This research was supported by grant from Jilin Scientific and Technological Development Program (Grant Number: 20210101197JC).

Author information

Author notes

  1. Linghua Yang and Ziyu Dong had equal contributions to the manuscript.

Authors and Affiliations

  1. Department of Endocrinology, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, Liaoning, China

    Linghua Yang,听Ziyu Dong听&听Shuman Yang

  2. Department of Epidemiology and Biostatistics, School of Public Health, Jilin University, Changchun, Jilin, China

    Linghua Yang,听Ziyu Dong,听Juan Zhang,听Xiaohua Zhang,听Xinyan Shi听&听Shuman Yang

  3. Department of Orthopaedics, The Second Hospital of Jilin University, Changchun, Jilin, China

    Baoming Yuan

  4. Magnetic Resonance Department, The FAW General Hospital of Jilin Province, Changchun, Jilin, China

    Jie Lei

  5. Department of Epidemiology and Biostatistics, School of Public Health, University of Nevada, Las Vegas, US

    Ann M. Vuong

Authors
  1. Linghua Yang

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  2. Ziyu Dong

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  3. Baoming Yuan

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  4. Jie Lei

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  5. Juan Zhang

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  6. Xiaohua Zhang

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  7. Xinyan Shi

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  8. Ann M. Vuong

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  9. Shuman Yang

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Contributions

SY had the conception for this research. BY and LY assessed the prevalence of comorbidity; XZ, XS, and AV assessed the network of comorbidity. SY, LY, and ZD wrote the main manuscript text. All authors reviewed and critically revised the manuscript, gave final approval of the version to be published, and agree to be accountable for all aspects of the works. All authors had final responsibility for the decision to submit for publication.

Corresponding author

Correspondence to Shuman Yang.

Ethics declarations

Ethics approval and consent to participate

This research project was approved by the ethics committee of China Medical University and the institutional review board (IRB) of The Second Hospital of Jilin University (Approval #: 2019-01-30). Our research adhered to the Declaration of Helsinki. All participants provided written informed consent before participating in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

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Yang, L., Dong, Z., Yuan, B. et al. Top comorbidities in osteoporotic fracture patients in a northeast population in China. 樱花视频 25, 1640 (2025). https://doi.org/10.1186/s12889-025-22331-0

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  • DOI: https://doi.org/10.1186/s12889-025-22331-0

Keywords

樱花视频

ISSN: 1471-2458

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