Assessment of Risk Factors for Fractures in Patients with Type 2 Diabetes over 60 Years Old: A Cross-Sectional Study from Northeast China
Aims. Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Yan Guo [verfasserIn] Yingfang Wang [verfasserIn] Feng Chen [verfasserIn] Jiabei Wang [verfasserIn] Difei Wang [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Übergeordnetes Werk: |
In: Journal of Diabetes Research - Hindawi Limited, 2013, (2020) |
|---|---|
| Übergeordnetes Werk: |
year:2020 |
| Links: |
Link aufrufen |
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| DOI / URN: |
10.1155/2020/1508258 |
|---|
| Katalog-ID: |
DOAJ005288266 |
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| 520 | |a Aims. Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk factors for common known fractures in particular diabetic populations. Methods. This cross-sectional study was conducted with community-dwelling people over 60 years old in nine communities from the city of Shenyang, which is the capital of Northeast China’s Liaoning Province. A total of 3430 elderly adults (2201 females, mean±standard deviation age 68.16±6.1 years; 1229 males, 69.16±6.7 years) were included. Our study measured the heel bone mineral density (BMD) and used the timed “up and go” (TUG) test and other indicators. In addition, we performed logistic regression analysis to explore the risk factors for fractures in the general population and the diabetic population and to analyze the differences. Results. The results revealed that a total of 201 elderly persons (5.8%), with an average age of 70.05±6.54 years, suffered from a history of fragility fractures, which affected more females (74.6%) than males (p=0.001). The prevalence of fractures in the T2DM population was 7.3%, which was much higher than the 5.2% in non-T2DM population (p<0.05). In the non-T2DM population, the BMD was lower and the TUG time was longer in the fracture group than in the nonfracture group (p<0.001). However, in the T2DM population, the BMD and TUG values were similar between the fracture group and the nonfracture group (p<0.05). Logistic regression analysis showed that the female sex (OR 1.835), TUG time<10.2 s (OR 1.602), and T‐score≤−2.5 (OR 1.750) were independent risk factors for fragility fractures in the non-T2DM population, but they were not risk factors in the T2DM population. Conclusions. This study found that low BMD and slow TUG time were independent risk factors for fractures in non-T2DM patients, while no associations were found in the T2DM population. Patients with T2DM have a higher risk for fractures even when they have sufficient BMD and a short TUG time. TUG and BMD underestimated the risk for fractures in the T2DM population. | ||
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10.1155/2020/1508258 doi (DE-627)DOAJ005288266 (DE-599)DOAJacc50132dd6e4819bee7450e3c3920da DE-627 ger DE-627 rakwb eng RC648-665 Yan Guo verfasserin aut Assessment of Risk Factors for Fractures in Patients with Type 2 Diabetes over 60 Years Old: A Cross-Sectional Study from Northeast China 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aims. Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk factors for common known fractures in particular diabetic populations. Methods. This cross-sectional study was conducted with community-dwelling people over 60 years old in nine communities from the city of Shenyang, which is the capital of Northeast China’s Liaoning Province. A total of 3430 elderly adults (2201 females, mean±standard deviation age 68.16±6.1 years; 1229 males, 69.16±6.7 years) were included. Our study measured the heel bone mineral density (BMD) and used the timed “up and go” (TUG) test and other indicators. In addition, we performed logistic regression analysis to explore the risk factors for fractures in the general population and the diabetic population and to analyze the differences. Results. The results revealed that a total of 201 elderly persons (5.8%), with an average age of 70.05±6.54 years, suffered from a history of fragility fractures, which affected more females (74.6%) than males (p=0.001). The prevalence of fractures in the T2DM population was 7.3%, which was much higher than the 5.2% in non-T2DM population (p<0.05). In the non-T2DM population, the BMD was lower and the TUG time was longer in the fracture group than in the nonfracture group (p<0.001). However, in the T2DM population, the BMD and TUG values were similar between the fracture group and the nonfracture group (p<0.05). Logistic regression analysis showed that the female sex (OR 1.835), TUG time<10.2 s (OR 1.602), and T‐score≤−2.5 (OR 1.750) were independent risk factors for fragility fractures in the non-T2DM population, but they were not risk factors in the T2DM population. Conclusions. This study found that low BMD and slow TUG time were independent risk factors for fractures in non-T2DM patients, while no associations were found in the T2DM population. Patients with T2DM have a higher risk for fractures even when they have sufficient BMD and a short TUG time. TUG and BMD underestimated the risk for fractures in the T2DM population. Diseases of the endocrine glands. Clinical endocrinology Yingfang Wang verfasserin aut Feng Chen verfasserin aut Jiabei Wang verfasserin aut Difei Wang verfasserin aut In Journal of Diabetes Research Hindawi Limited, 2013 (2020) (DE-627)742225437 (DE-600)2711897-6 23146753 nnns year:2020 https://doi.org/10.1155/2020/1508258 kostenfrei https://doaj.org/article/acc50132dd6e4819bee7450e3c3920da kostenfrei http://dx.doi.org/10.1155/2020/1508258 kostenfrei https://doaj.org/toc/2314-6745 Journal toc kostenfrei https://doaj.org/toc/2314-6753 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2020 |
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10.1155/2020/1508258 doi (DE-627)DOAJ005288266 (DE-599)DOAJacc50132dd6e4819bee7450e3c3920da DE-627 ger DE-627 rakwb eng RC648-665 Yan Guo verfasserin aut Assessment of Risk Factors for Fractures in Patients with Type 2 Diabetes over 60 Years Old: A Cross-Sectional Study from Northeast China 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aims. Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk factors for common known fractures in particular diabetic populations. Methods. This cross-sectional study was conducted with community-dwelling people over 60 years old in nine communities from the city of Shenyang, which is the capital of Northeast China’s Liaoning Province. A total of 3430 elderly adults (2201 females, mean±standard deviation age 68.16±6.1 years; 1229 males, 69.16±6.7 years) were included. Our study measured the heel bone mineral density (BMD) and used the timed “up and go” (TUG) test and other indicators. In addition, we performed logistic regression analysis to explore the risk factors for fractures in the general population and the diabetic population and to analyze the differences. Results. The results revealed that a total of 201 elderly persons (5.8%), with an average age of 70.05±6.54 years, suffered from a history of fragility fractures, which affected more females (74.6%) than males (p=0.001). The prevalence of fractures in the T2DM population was 7.3%, which was much higher than the 5.2% in non-T2DM population (p<0.05). In the non-T2DM population, the BMD was lower and the TUG time was longer in the fracture group than in the nonfracture group (p<0.001). However, in the T2DM population, the BMD and TUG values were similar between the fracture group and the nonfracture group (p<0.05). Logistic regression analysis showed that the female sex (OR 1.835), TUG time<10.2 s (OR 1.602), and T‐score≤−2.5 (OR 1.750) were independent risk factors for fragility fractures in the non-T2DM population, but they were not risk factors in the T2DM population. Conclusions. This study found that low BMD and slow TUG time were independent risk factors for fractures in non-T2DM patients, while no associations were found in the T2DM population. Patients with T2DM have a higher risk for fractures even when they have sufficient BMD and a short TUG time. TUG and BMD underestimated the risk for fractures in the T2DM population. Diseases of the endocrine glands. Clinical endocrinology Yingfang Wang verfasserin aut Feng Chen verfasserin aut Jiabei Wang verfasserin aut Difei Wang verfasserin aut In Journal of Diabetes Research Hindawi Limited, 2013 (2020) (DE-627)742225437 (DE-600)2711897-6 23146753 nnns year:2020 https://doi.org/10.1155/2020/1508258 kostenfrei https://doaj.org/article/acc50132dd6e4819bee7450e3c3920da kostenfrei http://dx.doi.org/10.1155/2020/1508258 kostenfrei https://doaj.org/toc/2314-6745 Journal toc kostenfrei https://doaj.org/toc/2314-6753 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2020 |
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10.1155/2020/1508258 doi (DE-627)DOAJ005288266 (DE-599)DOAJacc50132dd6e4819bee7450e3c3920da DE-627 ger DE-627 rakwb eng RC648-665 Yan Guo verfasserin aut Assessment of Risk Factors for Fractures in Patients with Type 2 Diabetes over 60 Years Old: A Cross-Sectional Study from Northeast China 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aims. Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk factors for common known fractures in particular diabetic populations. Methods. This cross-sectional study was conducted with community-dwelling people over 60 years old in nine communities from the city of Shenyang, which is the capital of Northeast China’s Liaoning Province. A total of 3430 elderly adults (2201 females, mean±standard deviation age 68.16±6.1 years; 1229 males, 69.16±6.7 years) were included. Our study measured the heel bone mineral density (BMD) and used the timed “up and go” (TUG) test and other indicators. In addition, we performed logistic regression analysis to explore the risk factors for fractures in the general population and the diabetic population and to analyze the differences. Results. The results revealed that a total of 201 elderly persons (5.8%), with an average age of 70.05±6.54 years, suffered from a history of fragility fractures, which affected more females (74.6%) than males (p=0.001). The prevalence of fractures in the T2DM population was 7.3%, which was much higher than the 5.2% in non-T2DM population (p<0.05). In the non-T2DM population, the BMD was lower and the TUG time was longer in the fracture group than in the nonfracture group (p<0.001). However, in the T2DM population, the BMD and TUG values were similar between the fracture group and the nonfracture group (p<0.05). Logistic regression analysis showed that the female sex (OR 1.835), TUG time<10.2 s (OR 1.602), and T‐score≤−2.5 (OR 1.750) were independent risk factors for fragility fractures in the non-T2DM population, but they were not risk factors in the T2DM population. Conclusions. This study found that low BMD and slow TUG time were independent risk factors for fractures in non-T2DM patients, while no associations were found in the T2DM population. Patients with T2DM have a higher risk for fractures even when they have sufficient BMD and a short TUG time. TUG and BMD underestimated the risk for fractures in the T2DM population. Diseases of the endocrine glands. Clinical endocrinology Yingfang Wang verfasserin aut Feng Chen verfasserin aut Jiabei Wang verfasserin aut Difei Wang verfasserin aut In Journal of Diabetes Research Hindawi Limited, 2013 (2020) (DE-627)742225437 (DE-600)2711897-6 23146753 nnns year:2020 https://doi.org/10.1155/2020/1508258 kostenfrei https://doaj.org/article/acc50132dd6e4819bee7450e3c3920da kostenfrei http://dx.doi.org/10.1155/2020/1508258 kostenfrei https://doaj.org/toc/2314-6745 Journal toc kostenfrei https://doaj.org/toc/2314-6753 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2020 |
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10.1155/2020/1508258 doi (DE-627)DOAJ005288266 (DE-599)DOAJacc50132dd6e4819bee7450e3c3920da DE-627 ger DE-627 rakwb eng RC648-665 Yan Guo verfasserin aut Assessment of Risk Factors for Fractures in Patients with Type 2 Diabetes over 60 Years Old: A Cross-Sectional Study from Northeast China 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aims. Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk factors for common known fractures in particular diabetic populations. Methods. This cross-sectional study was conducted with community-dwelling people over 60 years old in nine communities from the city of Shenyang, which is the capital of Northeast China’s Liaoning Province. A total of 3430 elderly adults (2201 females, mean±standard deviation age 68.16±6.1 years; 1229 males, 69.16±6.7 years) were included. Our study measured the heel bone mineral density (BMD) and used the timed “up and go” (TUG) test and other indicators. In addition, we performed logistic regression analysis to explore the risk factors for fractures in the general population and the diabetic population and to analyze the differences. Results. The results revealed that a total of 201 elderly persons (5.8%), with an average age of 70.05±6.54 years, suffered from a history of fragility fractures, which affected more females (74.6%) than males (p=0.001). The prevalence of fractures in the T2DM population was 7.3%, which was much higher than the 5.2% in non-T2DM population (p<0.05). In the non-T2DM population, the BMD was lower and the TUG time was longer in the fracture group than in the nonfracture group (p<0.001). However, in the T2DM population, the BMD and TUG values were similar between the fracture group and the nonfracture group (p<0.05). Logistic regression analysis showed that the female sex (OR 1.835), TUG time<10.2 s (OR 1.602), and T‐score≤−2.5 (OR 1.750) were independent risk factors for fragility fractures in the non-T2DM population, but they were not risk factors in the T2DM population. Conclusions. This study found that low BMD and slow TUG time were independent risk factors for fractures in non-T2DM patients, while no associations were found in the T2DM population. Patients with T2DM have a higher risk for fractures even when they have sufficient BMD and a short TUG time. TUG and BMD underestimated the risk for fractures in the T2DM population. Diseases of the endocrine glands. Clinical endocrinology Yingfang Wang verfasserin aut Feng Chen verfasserin aut Jiabei Wang verfasserin aut Difei Wang verfasserin aut In Journal of Diabetes Research Hindawi Limited, 2013 (2020) (DE-627)742225437 (DE-600)2711897-6 23146753 nnns year:2020 https://doi.org/10.1155/2020/1508258 kostenfrei https://doaj.org/article/acc50132dd6e4819bee7450e3c3920da kostenfrei http://dx.doi.org/10.1155/2020/1508258 kostenfrei https://doaj.org/toc/2314-6745 Journal toc kostenfrei https://doaj.org/toc/2314-6753 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2020 |
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10.1155/2020/1508258 doi (DE-627)DOAJ005288266 (DE-599)DOAJacc50132dd6e4819bee7450e3c3920da DE-627 ger DE-627 rakwb eng RC648-665 Yan Guo verfasserin aut Assessment of Risk Factors for Fractures in Patients with Type 2 Diabetes over 60 Years Old: A Cross-Sectional Study from Northeast China 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Aims. Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk factors for common known fractures in particular diabetic populations. Methods. This cross-sectional study was conducted with community-dwelling people over 60 years old in nine communities from the city of Shenyang, which is the capital of Northeast China’s Liaoning Province. A total of 3430 elderly adults (2201 females, mean±standard deviation age 68.16±6.1 years; 1229 males, 69.16±6.7 years) were included. Our study measured the heel bone mineral density (BMD) and used the timed “up and go” (TUG) test and other indicators. In addition, we performed logistic regression analysis to explore the risk factors for fractures in the general population and the diabetic population and to analyze the differences. Results. The results revealed that a total of 201 elderly persons (5.8%), with an average age of 70.05±6.54 years, suffered from a history of fragility fractures, which affected more females (74.6%) than males (p=0.001). The prevalence of fractures in the T2DM population was 7.3%, which was much higher than the 5.2% in non-T2DM population (p<0.05). In the non-T2DM population, the BMD was lower and the TUG time was longer in the fracture group than in the nonfracture group (p<0.001). However, in the T2DM population, the BMD and TUG values were similar between the fracture group and the nonfracture group (p<0.05). Logistic regression analysis showed that the female sex (OR 1.835), TUG time<10.2 s (OR 1.602), and T‐score≤−2.5 (OR 1.750) were independent risk factors for fragility fractures in the non-T2DM population, but they were not risk factors in the T2DM population. Conclusions. This study found that low BMD and slow TUG time were independent risk factors for fractures in non-T2DM patients, while no associations were found in the T2DM population. Patients with T2DM have a higher risk for fractures even when they have sufficient BMD and a short TUG time. TUG and BMD underestimated the risk for fractures in the T2DM population. Diseases of the endocrine glands. Clinical endocrinology Yingfang Wang verfasserin aut Feng Chen verfasserin aut Jiabei Wang verfasserin aut Difei Wang verfasserin aut In Journal of Diabetes Research Hindawi Limited, 2013 (2020) (DE-627)742225437 (DE-600)2711897-6 23146753 nnns year:2020 https://doi.org/10.1155/2020/1508258 kostenfrei https://doaj.org/article/acc50132dd6e4819bee7450e3c3920da kostenfrei http://dx.doi.org/10.1155/2020/1508258 kostenfrei https://doaj.org/toc/2314-6745 Journal toc kostenfrei https://doaj.org/toc/2314-6753 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2232 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 2020 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ005288266</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230309192105.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230225s2020 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1155/2020/1508258</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ005288266</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJacc50132dd6e4819bee7450e3c3920da</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">RC648-665</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Yan Guo</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Assessment of Risk Factors for Fractures in Patients with Type 2 Diabetes over 60 Years Old: A Cross-Sectional Study from Northeast China</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Aims. Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk factors for common known fractures in particular diabetic populations. Methods. This cross-sectional study was conducted with community-dwelling people over 60 years old in nine communities from the city of Shenyang, which is the capital of Northeast China’s Liaoning Province. A total of 3430 elderly adults (2201 females, mean±standard deviation age 68.16±6.1 years; 1229 males, 69.16±6.7 years) were included. Our study measured the heel bone mineral density (BMD) and used the timed “up and go” (TUG) test and other indicators. In addition, we performed logistic regression analysis to explore the risk factors for fractures in the general population and the diabetic population and to analyze the differences. Results. The results revealed that a total of 201 elderly persons (5.8%), with an average age of 70.05±6.54 years, suffered from a history of fragility fractures, which affected more females (74.6%) than males (p=0.001). The prevalence of fractures in the T2DM population was 7.3%, which was much higher than the 5.2% in non-T2DM population (p<0.05). In the non-T2DM population, the BMD was lower and the TUG time was longer in the fracture group than in the nonfracture group (p<0.001). However, in the T2DM population, the BMD and TUG values were similar between the fracture group and the nonfracture group (p<0.05). Logistic regression analysis showed that the female sex (OR 1.835), TUG time<10.2 s (OR 1.602), and T‐score≤−2.5 (OR 1.750) were independent risk factors for fragility fractures in the non-T2DM population, but they were not risk factors in the T2DM population. Conclusions. This study found that low BMD and slow TUG time were independent risk factors for fractures in non-T2DM patients, while no associations were found in the T2DM population. Patients with T2DM have a higher risk for fractures even when they have sufficient BMD and a short TUG time. TUG and BMD underestimated the risk for fractures in the T2DM population.</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Diseases of the endocrine glands. 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Yan Guo |
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RC648-665 Assessment of Risk Factors for Fractures in Patients with Type 2 Diabetes over 60 Years Old: A Cross-Sectional Study from Northeast China |
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assessment of risk factors for fractures in patients with type 2 diabetes over 60 years old: a cross-sectional study from northeast china |
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RC648-665 |
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Assessment of Risk Factors for Fractures in Patients with Type 2 Diabetes over 60 Years Old: A Cross-Sectional Study from Northeast China |
| abstract |
Aims. Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk factors for common known fractures in particular diabetic populations. Methods. This cross-sectional study was conducted with community-dwelling people over 60 years old in nine communities from the city of Shenyang, which is the capital of Northeast China’s Liaoning Province. A total of 3430 elderly adults (2201 females, mean±standard deviation age 68.16±6.1 years; 1229 males, 69.16±6.7 years) were included. Our study measured the heel bone mineral density (BMD) and used the timed “up and go” (TUG) test and other indicators. In addition, we performed logistic regression analysis to explore the risk factors for fractures in the general population and the diabetic population and to analyze the differences. Results. The results revealed that a total of 201 elderly persons (5.8%), with an average age of 70.05±6.54 years, suffered from a history of fragility fractures, which affected more females (74.6%) than males (p=0.001). The prevalence of fractures in the T2DM population was 7.3%, which was much higher than the 5.2% in non-T2DM population (p<0.05). In the non-T2DM population, the BMD was lower and the TUG time was longer in the fracture group than in the nonfracture group (p<0.001). However, in the T2DM population, the BMD and TUG values were similar between the fracture group and the nonfracture group (p<0.05). Logistic regression analysis showed that the female sex (OR 1.835), TUG time<10.2 s (OR 1.602), and T‐score≤−2.5 (OR 1.750) were independent risk factors for fragility fractures in the non-T2DM population, but they were not risk factors in the T2DM population. Conclusions. This study found that low BMD and slow TUG time were independent risk factors for fractures in non-T2DM patients, while no associations were found in the T2DM population. Patients with T2DM have a higher risk for fractures even when they have sufficient BMD and a short TUG time. TUG and BMD underestimated the risk for fractures in the T2DM population. |
| abstractGer |
Aims. Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk factors for common known fractures in particular diabetic populations. Methods. This cross-sectional study was conducted with community-dwelling people over 60 years old in nine communities from the city of Shenyang, which is the capital of Northeast China’s Liaoning Province. A total of 3430 elderly adults (2201 females, mean±standard deviation age 68.16±6.1 years; 1229 males, 69.16±6.7 years) were included. Our study measured the heel bone mineral density (BMD) and used the timed “up and go” (TUG) test and other indicators. In addition, we performed logistic regression analysis to explore the risk factors for fractures in the general population and the diabetic population and to analyze the differences. Results. The results revealed that a total of 201 elderly persons (5.8%), with an average age of 70.05±6.54 years, suffered from a history of fragility fractures, which affected more females (74.6%) than males (p=0.001). The prevalence of fractures in the T2DM population was 7.3%, which was much higher than the 5.2% in non-T2DM population (p<0.05). In the non-T2DM population, the BMD was lower and the TUG time was longer in the fracture group than in the nonfracture group (p<0.001). However, in the T2DM population, the BMD and TUG values were similar between the fracture group and the nonfracture group (p<0.05). Logistic regression analysis showed that the female sex (OR 1.835), TUG time<10.2 s (OR 1.602), and T‐score≤−2.5 (OR 1.750) were independent risk factors for fragility fractures in the non-T2DM population, but they were not risk factors in the T2DM population. Conclusions. This study found that low BMD and slow TUG time were independent risk factors for fractures in non-T2DM patients, while no associations were found in the T2DM population. Patients with T2DM have a higher risk for fractures even when they have sufficient BMD and a short TUG time. TUG and BMD underestimated the risk for fractures in the T2DM population. |
| abstract_unstemmed |
Aims. Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk factors for common known fractures in particular diabetic populations. Methods. This cross-sectional study was conducted with community-dwelling people over 60 years old in nine communities from the city of Shenyang, which is the capital of Northeast China’s Liaoning Province. A total of 3430 elderly adults (2201 females, mean±standard deviation age 68.16±6.1 years; 1229 males, 69.16±6.7 years) were included. Our study measured the heel bone mineral density (BMD) and used the timed “up and go” (TUG) test and other indicators. In addition, we performed logistic regression analysis to explore the risk factors for fractures in the general population and the diabetic population and to analyze the differences. Results. The results revealed that a total of 201 elderly persons (5.8%), with an average age of 70.05±6.54 years, suffered from a history of fragility fractures, which affected more females (74.6%) than males (p=0.001). The prevalence of fractures in the T2DM population was 7.3%, which was much higher than the 5.2% in non-T2DM population (p<0.05). In the non-T2DM population, the BMD was lower and the TUG time was longer in the fracture group than in the nonfracture group (p<0.001). However, in the T2DM population, the BMD and TUG values were similar between the fracture group and the nonfracture group (p<0.05). Logistic regression analysis showed that the female sex (OR 1.835), TUG time<10.2 s (OR 1.602), and T‐score≤−2.5 (OR 1.750) were independent risk factors for fragility fractures in the non-T2DM population, but they were not risk factors in the T2DM population. Conclusions. This study found that low BMD and slow TUG time were independent risk factors for fractures in non-T2DM patients, while no associations were found in the T2DM population. Patients with T2DM have a higher risk for fractures even when they have sufficient BMD and a short TUG time. TUG and BMD underestimated the risk for fractures in the T2DM population. |
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Assessment of Risk Factors for Fractures in Patients with Type 2 Diabetes over 60 Years Old: A Cross-Sectional Study from Northeast China |
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https://doi.org/10.1155/2020/1508258 https://doaj.org/article/acc50132dd6e4819bee7450e3c3920da http://dx.doi.org/10.1155/2020/1508258 https://doaj.org/toc/2314-6745 https://doaj.org/toc/2314-6753 |
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Yingfang Wang Feng Chen Jiabei Wang Difei Wang |
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Yingfang Wang Feng Chen Jiabei Wang Difei Wang |
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742225437 |
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RC - Internal Medicine |
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| doi_str |
10.1155/2020/1508258 |
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RC648-665 |
| up_date |
2024-07-03T14:06:47.410Z |
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1803567085558693888 |
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Previous evidence has demonstrated an increased fracture risk among the population with type 2 diabetes mellitus (T2DM). This study investigated the prevalence of bone fractures in elderly subjects (with and without type 2 diabetes) and identified any fracture risk factors, especially the risk factors for common known fractures in particular diabetic populations. Methods. This cross-sectional study was conducted with community-dwelling people over 60 years old in nine communities from the city of Shenyang, which is the capital of Northeast China’s Liaoning Province. A total of 3430 elderly adults (2201 females, mean±standard deviation age 68.16±6.1 years; 1229 males, 69.16±6.7 years) were included. Our study measured the heel bone mineral density (BMD) and used the timed “up and go” (TUG) test and other indicators. In addition, we performed logistic regression analysis to explore the risk factors for fractures in the general population and the diabetic population and to analyze the differences. Results. The results revealed that a total of 201 elderly persons (5.8%), with an average age of 70.05±6.54 years, suffered from a history of fragility fractures, which affected more females (74.6%) than males (p=0.001). The prevalence of fractures in the T2DM population was 7.3%, which was much higher than the 5.2% in non-T2DM population (p<0.05). In the non-T2DM population, the BMD was lower and the TUG time was longer in the fracture group than in the nonfracture group (p<0.001). However, in the T2DM population, the BMD and TUG values were similar between the fracture group and the nonfracture group (p<0.05). Logistic regression analysis showed that the female sex (OR 1.835), TUG time<10.2 s (OR 1.602), and T‐score≤−2.5 (OR 1.750) were independent risk factors for fragility fractures in the non-T2DM population, but they were not risk factors in the T2DM population. Conclusions. This study found that low BMD and slow TUG time were independent risk factors for fractures in non-T2DM patients, while no associations were found in the T2DM population. Patients with T2DM have a higher risk for fractures even when they have sufficient BMD and a short TUG time. TUG and BMD underestimated the risk for fractures in the T2DM population.</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Diseases of the endocrine glands. 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