1.A study on the Charlson comorbidity index and health-related quality of life in the middle-aged and elderly osteoporosis population.
Xu WEI ; Xin-Yi HUANG ; Yi-Li ZHANG ; Li-Guo ZHU ; Hao SHEN ; Yan-Ming XIE
China Journal of Orthopaedics and Traumatology 2023;36(2):145-150
		                        		
		                        			OBJECTIVE:
		                        			To explore the characteristics of comorbidities in patients with osteoporosis(OP) and factors associated health-related quality of life, so as to provide decision-making reference for improving the ability of disease co-prevention and co-treatment and the patient's life-cycle quality of life.
		                        		
		                        			METHODS:
		                        			From November 2017 to July 2018, clinical information and biological samples from residents in 10 communities in Chaoyang District and Fengtai Distric of Beijing were collected, and bone density testing was conducted. Based on the Charlson comorbidity index (CCI), the comorbidity of the population was quantified, and grouped according to factors such as gender, age, and the differences between the groups were explored. Combined with the clinical information of patients, the difference characteristics of comorbidity and non-comorbidity population were analyzed. Pearson/Spearman correlation analysis and binary Logistic regression analysis were used to explore the factors affecting the health-related quality of life in patients with OP.
		                        		
		                        			RESULTS:
		                        			Among the 521 OP patients, 121 patients had no comorbidities, and there were 153, 106, 65, and 30 patients with one, two, three, and four comorbidities, respectively, 46 patients with 5 or more kinds of comorbidites. Hypertension was the most common comorbidity in OP patients, accounting for 21.60%;followed by hyperlipidemia, accounting for 13.51%. The most common combination of the two diseases was hypertension plus hyperlipidemia (64 cases, 12.28%). Through the analysis of differences between age groups, it was found that the older patients, showed higher the CCI, and the difference between groups was statistically significant(Z=1.93, P=0.05). There were significant differences in the total EQ-5D score and the dimensions of anxiety and depression between patients with comorbidities (CCI≠0) and non-comorbidities (CCI=0) (Z=-2.67, P=0.01;Z=-2.44, P=0.02). Correlation analysis found that CCI, history of fracture, history of falls, hip bone mineral density T value and parathyroid hormone were all related to the health-related quality of life in OP patients (P<0.05). Binary Logistic regression analysis suggested that the right hip bone mineral density T value (P=0.02), CCI (P=0.01), fracture history (P=0.03) and fall history (P=0.01) were the risk factors that affect the health-related quality of life in OP patients.
		                        		
		                        			CONCLUSION
		                        			The burden of comorbidities among middle-aged and elderly OP populations in Beijing is relatively heavy, and the health management of such populations should be further strengthened, specifically the combination of multiple comorbidities should be given high priority. Comorbid factors are of great importance for the diagnosis and treatment strategy of OP patients, which could further improve the quality of life.
		                        		
		                        		
		                        		
		                        			Aged
		                        			;
		                        		
		                        			Middle Aged
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Quality of Life
		                        			;
		                        		
		                        			Osteoporosis/epidemiology*
		                        			;
		                        		
		                        			Comorbidity
		                        			;
		                        		
		                        			Risk Factors
		                        			;
		                        		
		                        			Fractures, Bone
		                        			;
		                        		
		                        			Hypertension/epidemiology*
		                        			
		                        		
		                        	
2.Correlation analysis between body mass index and clinical characteristics of rheumatoid arthritis.
Jing Feng ZHANG ; Yin Ji JIN ; Hui WEI ; Zhong Qiang YAO ; Jin Xia ZHAO
Journal of Peking University(Health Sciences) 2023;55(6):993-999
		                        		
		                        			OBJECTIVE:
		                        			To analyze the clinical features of overweight and obese rheumatoid arthritis (RA)patients, and the relationship between body mass index (BMI) and disease characteristics.
		                        		
		                        			METHODS:
		                        			The demographic data, extra-articular manifestations, comorbidities, and disease activity of RA patients admitted to the Rheumatology and Immunology Department of Peking University Third Hospital from January 2015 to December 2020 were collected, and the above characteristics of overweight and obese RA patients were retrospectively analyzed. According to the WHO, BMI≥30 kg/m2 referred to obese individuals, 25≤BMI < 30 kg/m2 referred to overweight individuals, 18.5≤BMI < 25 kg/m2 referred to normal individuals, BMI < 18.5 kg/m2 referred to reduced body mass individuals. t test was used for the quantitative data in accordance with normal distribution. Wilcoxon rank sum test was used for the quantitative data of non-normal distribution. The qualitative data were analyzed by chi square test. But while 1≤theoretical frequency < 5, Chi square test of corrected four grid table was used. And Fisher exact probability method was used when theoretical frequency < 1. Analyzing whether overweight or obesity was associated with comorbidities using Logistic regression adjusted confounding factors.
		                        		
		                        			RESULTS:
		                        			A total of 481 RA patients were included in this study, with an average BMI value of (23.28±3.75) kg/m2.Of the patients, 31 cases (6.5%) were with BMI < 18.5 kg/m2, 309 cases (64.2%) with 18.5≤ BMI < 25 kg/m2, amounting to 340 cases (70.7%). There were 119 overweight individuals (25≤ BMI < 30 kg/m2, 24.7%) and 22 obese individuals (BMI≥30 kg/m2, 4.6%), totaling 141 (29.3%).The proportion of the overweight and obese RA patients suffering from hypertension (57.4% vs. 39.1%, P < 0.001), diabetes (25.5% vs. 15.0%, P=0.006), hyperlipidemia (22.7% vs. 10.9%, P=0.001), fatty liver (28.4% vs. 7.4%, P < 0.001), osteoarthritis (39.0% vs. 29.4%, P=0.040) was significantly higher, and the proportion of the patients with osteoporosis(59.6% vs. 70.9%, P=0.016) and anemia (36.2% vs. 55.6%, P < 0.001) was significantly lower. However, there was no difference between the two groups in coronary heart disease (5.7% vs. 7.6%, P=0.442), cerebrovascular disease (6.4% vs. 8.8%, P=0.372) and peripheral atherosclerosis (9.2% vs. 7.6%, P=0.565).The median C-reactive protein (CRP, 1.52 mg/dL vs. 2.35 mg/dL, P=0.008), median erythrocyte sedimentation rate (ESR, 34.0 mm/h vs. 50.0 mm/h, P=0.003), pain visual simulation score (VAS) (3.66±3.08 vs. 4.40±2.85, P=0.011), and 28 joint disease activity scores (DAS-28, 5.05±1.60 vs. 5.45±1.52, P=0.010) in the overweight and obese RA group were all lower than those in the normal and reduced weight groups. Multivariate regression analysis showed that overweight and obesity was an independent risk factor for hypertension, diabetes, hyperlipidemia and fatty liver, and had protective effects on osteoporosis and anemia.
		                        		
		                        			CONCLUSION
		                        			In RA patients, RA disease activity is lower in overweight and obesity patients. Overweight and obesity is associated with hypertension, diabetes and hyperlipidemia, but not with cardiovascular and cerebrovascular diseases.
		                        		
		                        		
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Body Mass Index
		                        			;
		                        		
		                        			Overweight/epidemiology*
		                        			;
		                        		
		                        			Retrospective Studies
		                        			;
		                        		
		                        			Arthritis, Rheumatoid/epidemiology*
		                        			;
		                        		
		                        			Obesity/epidemiology*
		                        			;
		                        		
		                        			Diabetes Mellitus
		                        			;
		                        		
		                        			Hypertension/complications*
		                        			;
		                        		
		                        			Fatty Liver/complications*
		                        			;
		                        		
		                        			Hyperlipidemias/complications*
		                        			;
		                        		
		                        			Osteoporosis/complications*
		                        			;
		                        		
		                        			Anemia
		                        			
		                        		
		                        	
3.Prevalence of osteoporosis and related factors in postmenopausal women aged 40 and above in China.
Shu Nyu TANG ; Xiang Jun YIN ; Wei YU ; Lu CUI ; Zhi Xin LI ; Li Jia CUI ; Lin Hong WANG ; Wei Bo XIA
Chinese Journal of Epidemiology 2022;43(4):509-516
		                        		
		                        			
		                        			Objective: To understand the prevalence of osteoporosis and related factors in postmenopausal women aged ≥40 years in China and provide scientific evidence for osteoporosis prevention and control. Methods: Data of this study were from the 2018 China Osteoporosis Epidemiological Survey, covering 44 counties (districts) in 11 provinces in China. Related variables were collected by questionnaire survey and physical measurement, and the BMD of lumbar spine and proximal femur was measured by dual-energy X-ray absorption method. The prevalence of osteoporosis and its 95%CI in postmenopausal women aged ≥40 years were estimated with complex sampling weights. Results: A total of 5 728 postmenopausal women aged ≥40 years were included in the analysis and the prevalence of osteoporosis was 32.5% (95%CI: 30.3%-34.7%). The prevalence of osteoporosis in postmenopausal women aged 40-49 years, 50-59 years, 60-69 years, 70-79 years, and ≥80 years were 16.0% (95%CI:4.5%-27.5%), 18.4% (95%CI:15.9%-20.8%), 37.5% (95%CI:34.5%-40.4%), 52.9% (95%CI: 47.5%-58.3%), and 68.0% (95%CI:55.9%-80.1%) respectively. The prevalence of osteoporosis was higher (P<0.001) in those with education level of primary school or below (47.2%, 95%CI: 43.0%-51.3%) and in those with individual annual income less than 10 000 Yuan, (40.3%, 95%CI: 36.9%-43.7%). The prevalence of osteoporosis was 35.1% in rural areas (95%CI: 32.0%-38.1%), which was higher than that in urban areas (P<0.001). The prevalence of osteoporosis in low weight, normal weight, overweight and obese groups were 69.9% (95%CI: 59.0%-80.8%), 42.2% (95%CI: 38.7%-45.7%), 24.2% (95%CI: 21.3%-27.1%) and 14.6% (95%CI: 11.1%-18.0%), respectively. The prevalence of osteoporosis in those with menstrual maintenance years ≤30 years and in those with menopause years ≥11 years were 46.1% (95%CI:40.8%-51.3%) and 48.2% (95%CI:45.0%-51.3%), respectively. Multivariate logistic analysis showed that age ≥60 years, education level of primary school or below, annual household income per capita less than 10 000 Yuan, low body weight, menstrual maintenance years ≤30 years, menopause years ≥11 years were risk factors of osteoporosis in postmenopausal women in China. Conclusions: The prevalence of osteoporosis was high in postmenopausal women aged ≥40 years in China, and there were differences in osteoporosis prevalence among different socioeconomic groups. Effective interventions should be taken for the prevention and control of osteoporosis in key groups in the future.
		                        		
		                        		
		                        		
		                        			Absorptiometry, Photon
		                        			;
		                        		
		                        			Bone Density
		                        			;
		                        		
		                        			China/epidemiology*
		                        			;
		                        		
		                        			Female
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Lumbar Vertebrae
		                        			;
		                        		
		                        			Osteoporosis/epidemiology*
		                        			;
		                        		
		                        			Osteoporosis, Postmenopausal/etiology*
		                        			;
		                        		
		                        			Postmenopause
		                        			;
		                        		
		                        			Prevalence
		                        			;
		                        		
		                        			Risk Factors
		                        			
		                        		
		                        	
4.Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis.
Yaxin CHEN ; Tianyi YANG ; Xiaofeng GAO ; Ajing XU
Frontiers of Medicine 2022;16(3):496-506
		                        		
		                        			
		                        			The fracture risk of patients with diabetes is higher than those of patients without diabetes due to hyperglycemia, usage of diabetes drugs, changes in insulin levels, and excretion, and this risk begins as early as adolescence. Many factors including demographic data (such as age, height, weight, and gender), medical history (such as smoking, drinking, and menopause), and examination (such as bone mineral density, blood routine, and urine routine) may be related to bone metabolism in patients with diabetes. However, most of the existing methods are qualitative assessments and do not consider the interactions of the physiological factors of humans. In addition, the fracture risk of patients with diabetes and osteoporosis has not been further studied previously. In this paper, a hybrid model combining XGBoost with deep neural network is used to predict the fracture risk of patients with diabetes and osteoporosis, and investigate the effect of patients' physiological factors on fracture risk. A total of 147 raw input features are considered in our model. The presented model is compared with several benchmarks based on various metrics to prove its effectiveness. Moreover, the top 18 influencing factors of fracture risks of patients with diabetes are determined.
		                        		
		                        		
		                        		
		                        			Bone Density
		                        			;
		                        		
		                        			Deep Learning
		                        			;
		                        		
		                        			Diabetes Mellitus/epidemiology*
		                        			;
		                        		
		                        			Female
		                        			;
		                        		
		                        			Fractures, Bone/etiology*
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Osteoporosis/complications*
		                        			;
		                        		
		                        			Risk Factors
		                        			
		                        		
		                        	
5.Determinants of bone health in elderly Japanese men: study design and key findings of the Fujiwara-kyo Osteoporosis Risk in Men (FORMEN) cohort study.
Yuki FUJITA ; Junko TAMAKI ; Katsuyasu KOUDA ; Akiko YURA ; Yuho SATO ; Takahiro TACHIKI ; Masami HAMADA ; Etsuko KAJITA ; Kuniyasu KAMIYA ; Kazuki KAJI ; Koji TSUDA ; Kumiko OHARA ; Jong-Seong MOON ; Jun KITAGAWA ; Masayuki IKI
Environmental Health and Preventive Medicine 2021;26(1):51-51
		                        		
		                        			BACKGROUND:
		                        			The Fujiwara-kyo Osteoporosis Risk in Men (FORMEN) study was launched to investigate risk factors for osteoporotic fractures, interactions of osteoporosis with other non-communicable chronic diseases, and effects of fracture on QOL and mortality.
		                        		
		                        			METHODS:
		                        			FORMEN baseline study participants (in 2007 and 2008) included 2012 community-dwelling men (aged 65-93 years) in Nara prefecture, Japan. Clinical follow-up surveys were conducted 5 and 10 years after the baseline survey, and 1539 and 906 men completed them, respectively. Supplemental mail, telephone, and visit surveys were conducted with non-participants to obtain outcome information. Survival and fracture outcomes were determined for 2006 men, with 566 deaths identified and 1233 men remaining in the cohort at 10-year follow-up.
		                        		
		                        			COMMENTS
		                        			The baseline survey covered a wide range of bone health-related indices including bone mineral density, trabecular microarchitecture assessment, vertebral imaging for detecting vertebral fractures, and biochemical markers of bone turnover, as well as comprehensive geriatric assessment items. Follow-up surveys were conducted to obtain outcomes including osteoporotic fracture, cardiovascular diseases, initiation of long-term care, and mortality. A complete list of publications relating to the FORMEN study can be found at https://www.med.kindai.ac.jp/pubheal/FORMEN/Publications.html .
		                        		
		                        		
		                        		
		                        			Aged
		                        			;
		                        		
		                        			Bone Density
		                        			;
		                        		
		                        			Cardiovascular Diseases/etiology*
		                        			;
		                        		
		                        			Cohort Studies
		                        			;
		                        		
		                        			Geriatric Assessment
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Independent Living
		                        			;
		                        		
		                        			Japan/epidemiology*
		                        			;
		                        		
		                        			Long-Term Care/statistics & numerical data*
		                        			;
		                        		
		                        			Male
		                        			;
		                        		
		                        			Middle Aged
		                        			;
		                        		
		                        			Osteoporosis/etiology*
		                        			;
		                        		
		                        			Osteoporotic Fractures/etiology*
		                        			;
		                        		
		                        			Risk Factors
		                        			
		                        		
		                        	
6.Factors influencing peak bone mass gain.
Frontiers of Medicine 2021;15(1):53-69
		                        		
		                        			
		                        			Bone mass is a key determinant of osteoporosis and fragility fractures. Epidemiologic studies have shown that a 10% increase in peak bone mass (PBM) at the population level reduces the risk of fracture later in life by 50%. Low PBM is possibly due to the bone loss caused by various conditions or processes that occur during adolescence and young adulthood. Race, gender, and family history (genetics) are responsible for the majority of PBM, but other factors, such as physical activity, calcium and vitamin D intake, weight, smoking and alcohol consumption, socioeconomic status, age at menarche, and other secondary causes (diseases and medications), play important roles in PBM gain during childhood and adolescence. Hence, the optimization of lifestyle factors that affect PBM and bone strength is an important strategy to maximize PBM among adolescents and young people, and thus to reduce the low bone mass or osteoporosis risk in later life. This review aims to summarize the available evidence for the common but important factors that influence bone mass gain during growth and development and discuss the advances of developing high PBM.
		                        		
		                        		
		                        		
		                        			Adolescent
		                        			;
		                        		
		                        			Adult
		                        			;
		                        		
		                        			Bone Density
		                        			;
		                        		
		                        			Bone and Bones
		                        			;
		                        		
		                        			Child
		                        			;
		                        		
		                        			Exercise
		                        			;
		                        		
		                        			Female
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Life Style
		                        			;
		                        		
		                        			Osteoporosis/epidemiology*
		                        			;
		                        		
		                        			Risk Factors
		                        			;
		                        		
		                        			Young Adult
		                        			
		                        		
		                        	
7.The association of potassium intake with bone mineral density and the prevalence of osteoporosis among older Korean adults
Jinwoo HA ; Seong Ah KIM ; Kyungjoon LIM ; Sangah SHIN
Nutrition Research and Practice 2020;14(1):55-61
		                        		
		                        			
		                        			Osteoporosis is characterized by low bone mass and results in vulnerability to fracture. Calcium and vitamin D are known to play an important role in bone health. Recently, potassium has been identified as another important factor in skeletal health. We examined the link between potassium intake and bone health among the Korean older adult population.SUBJECTS/METHODS: This retrospective, cross-sectional study included 8,732 men and postmenopausal women over 50 years old who completed the Korean National Health and Nutrition Survey (KNHANES) between 2008 and 2011. Potassium consumption was evaluated using a 24-hour recall method. Bone mineral density (BMD) was measured at three sites (total hip, femur neck, and lumbar spine) by dual-energy X-ray absorptiometry (DEXA). Multinomial logistic regression was used to examine the link between potassium intake and prevalence of osteoporosis and osteopenia, after controlling for potential confounding variables.RESULTS: The BMD of the total femur and Ward's triangle were significantly different according to the potassium intake among men (P = 0.031 and P = 0.010, respectively). Women in the top tertile for potassium intake showed higher BMD than those in the bottom tertile at all measurement sites (all P < 0.05). Daily potassium intake was significantly related to a decreased risk of osteoporosis at the lumbar spine in postmenopausal women (odds ratios: 0.68, 95% confidence interval: 0.48-0.96, P trend = 0.031). However, the dietary potassium level was not related to the risk of osteoporosis in men.CONCLUSION: Current findings indicate that higher dietary potassium levels have a favorable effect on bone health and preventing osteoporosis in older Korean women.]]>
		                        		
		                        		
		                        		
		                        			Absorptiometry, Photon
		                        			;
		                        		
		                        			Adult
		                        			;
		                        		
		                        			Bone Density
		                        			;
		                        		
		                        			Bone Diseases, Metabolic
		                        			;
		                        		
		                        			Calcium
		                        			;
		                        		
		                        			Confounding Factors (Epidemiology)
		                        			;
		                        		
		                        			Cross-Sectional Studies
		                        			;
		                        		
		                        			Epidemiology
		                        			;
		                        		
		                        			Female
		                        			;
		                        		
		                        			Femur
		                        			;
		                        		
		                        			Femur Neck
		                        			;
		                        		
		                        			Hip
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Logistic Models
		                        			;
		                        		
		                        			Male
		                        			;
		                        		
		                        			Methods
		                        			;
		                        		
		                        			Nutrition Surveys
		                        			;
		                        		
		                        			Osteoporosis
		                        			;
		                        		
		                        			Population Surveillance
		                        			;
		                        		
		                        			Potassium
		                        			;
		                        		
		                        			Potassium, Dietary
		                        			;
		                        		
		                        			Prevalence
		                        			;
		                        		
		                        			Retrospective Studies
		                        			;
		                        		
		                        			Spine
		                        			;
		                        		
		                        			Vitamin D
		                        			
		                        		
		                        	
8.Evaluation of bone mass and relevance ratio of osteoporosis among middle aged and elderly population in Beijing community.
Yi-Li ZHANG ; Xu WEI ; Yan-Ming XIE ; Li-Guo ZHU ; Jing-Hua GAO ; Hao SHEN ; Yan CHAI ; Meng-Hua SUN ; Cheng ZHANG ; Kai SUN ; Bin TANG ; Jun-Jie JIANG ; Ying-Jie ZHI ; Chen-Chen YU
China Journal of Orthopaedics and Traumatology 2020;33(10):916-921
		                        		
		                        			OBJECTIVE:
		                        			To investigate the relevance ratio of osteoporosis and bone mass of middle aged and elderly people in Beijing communities, in order to understand occurrence and development trend of abnormality of bone mass in high-risk population from community.
		                        		
		                        			METHODS:
		                        			Based on the method of cross-sectional investigation, the information data of 1 540 middle-aged and elderly people from 10 communities were collected, including 415 males and 1 125 females, aged from 45 to 80 years old with the average of (63.02±7.15) years old; the height was (161.34±7.24) cm, the weight was (65.90±10.19) kg, body mass index was (25.29±3.32) kg /m2. Bone mineral density (BMD) of lumbar vertebrae (L
		                        		
		                        			RESULTS:
		                        			The level of β-CTX was(0.27±0.12) ng /ml, procollanen type 1 N-terminal propeptide(P1NP) was(51.03± 22.36) ng /ml, 25(OH) D3 was (16.68±6.24) ng /ml, serum calcium was(2.34±0.09) mmol / L, blood phosphorus was (1.43± 0.37) mmol / L, and blood magnesium was (0.94±0.07) mmol / L, alkaline phosphatase was (79.28±20.48) U/ L, parathyroid hormone was (3.09±1.60) pmol / L, osteocalcin was (13.29±6.65) ng /ml. Except for blood magnesium, the other indexes had significant differences between different sex groups(
		                        		
		                        			CONCLUSION
		                        			There are obvious differences in relevance ratio of osteoporosis and low bone mass among different sites. It is suggested that the clinical diagnosis of osteoporosis should be combined with bone mineral density and bone metabolic markers. With the increasing prevalence of osteoporosis among middle aged and elderly people in Beijing community, continuous follow-up research based on community primary health care units could promote early examination, early diagnosis, and early treatment of middle aged and elderly people at high risk of osteoporosis in community.
		                        		
		                        		
		                        		
		                        			Absorptiometry, Photon
		                        			;
		                        		
		                        			Aged
		                        			;
		                        		
		                        			Aged, 80 and over
		                        			;
		                        		
		                        			Beijing/epidemiology*
		                        			;
		                        		
		                        			Bone Density
		                        			;
		                        		
		                        			Cross-Sectional Studies
		                        			;
		                        		
		                        			Female
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Male
		                        			;
		                        		
		                        			Middle Aged
		                        			;
		                        		
		                        			Osteoporosis/epidemiology*
		                        			
		                        		
		                        	
9.Epidemiology of fragility hip fractures in Nan, Thailand
Worapong SUCHARITPONGPAN ; Nuttorn DARAPHONGSATAPORN ; Surapot SALOA ; Nattaphon PHILAWUTH ; Prapan CHONYUEN ; Kaiwan SRIRUANTHONG ; Krairoek WAIWATTANA
Osteoporosis and Sarcopenia 2019;5(1):19-22
		                        		
		                        			
		                        			OBJECTIVES: Hip fracture is the most serious consequence of falling in elderly with osteoporosis. Patients with hip fractures suffer functional deterioration and increased morbidity especially during the first year after fracture. Rapid increase in the proportion of the elderly increases the prevalence of hip fractures in Thailand, leading to major problem for public health. There is substantial variation in the incidence of hip fracture in different regions of Thailand. Demographic data are required to improve management and prevention. This study was aimed to describe the demographic data and to determine the incidence of fragility hip fractures in Nan, Thailand. METHODS: A retrospective, cohort study had been conducted in Nan and Pua hospital. Patients with hip fractures were sorted by International Classification of Diseases 10th Revision (S72.0–S72.2) from September 1, 2014 to December 31, 2017. Statistical analyses were conducted using descriptive analysis and 95% confidence interval. RESULTS: The incidence of hip fractures in Nan province in 2015–2017 were 211.6, 214.9 and 238.5 per 100,000 person-years, respectively. There were 876 patients in this study. Higher incidence was found in female (ratio, 2.5:1). About 87.2% of the fracture occurred inside the house. There were 5.9% who had refracture. The median for refracture time was 143 weeks. CONCLUSIONS: The incidence of hip fractures in Nan province was classified as moderate severity and was increasing between 2015 and 2017. A coordinated, multidisciplinary approach in homecare management especially in fall prevention are important factors to reduce incidence of fragility hip fracture.
		                        		
		                        		
		                        		
		                        			Accidental Falls
		                        			;
		                        		
		                        			Aged
		                        			;
		                        		
		                        			Cohort Studies
		                        			;
		                        		
		                        			Epidemiology
		                        			;
		                        		
		                        			Female
		                        			;
		                        		
		                        			Hip Fractures
		                        			;
		                        		
		                        			Hip
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Incidence
		                        			;
		                        		
		                        			International Classification of Diseases
		                        			;
		                        		
		                        			Osteoporosis
		                        			;
		                        		
		                        			Prevalence
		                        			;
		                        		
		                        			Public Health
		                        			;
		                        		
		                        			Retrospective Studies
		                        			;
		                        		
		                        			Thailand
		                        			
		                        		
		                        	
10.Diabetes and bone
Katrine HYGUM ; Jakob STARUP-LINDE ; Bente L LANGDAHL
Osteoporosis and Sarcopenia 2019;5(2):29-37
		                        		
		                        			
		                        			Bone disease is a serious complication to diabetes. Patients with type 1 diabetes (T1D) and type 2 diabetes (T2D) suffer from an increased risk of fracture, most notably at the hip, compared with patients without diabetes. Confounders such as patient sex, age, body mass index, blood glucose status, fall risk, and diabetes medications may influence the fracture risk. Different underlying mechanisms contribute to bone disease in patients with diabetes. Bone quality is affected by low bone turnover in T1D and T2D, and furthermore, incorporation of advanced glycation end-products, changes in the incretin hormone response, and microvascular complications contribute to impaired bone quality and increased fracture risk. Diagnosis of bone disease in patients with diabetes is a challenge as current methods for fracture prediction such as bone mineral density T-score and fracture risk assessment tools underestimate fracture risk for patients with T1D and T2D. This review focuses on bone disease and fracture risk in patients with diabetes regarding epidemiology, underlying disease mechanisms, and diagnostic methods, and we also provide considerations regarding the management of diabetes patients with bone disease in terms of an intervention threshold and different treatments.
		                        		
		                        		
		                        		
		                        			Blood Glucose
		                        			;
		                        		
		                        			Body Mass Index
		                        			;
		                        		
		                        			Bone Density
		                        			;
		                        		
		                        			Bone Diseases
		                        			;
		                        		
		                        			Bone Remodeling
		                        			;
		                        		
		                        			Diagnosis
		                        			;
		                        		
		                        			Epidemiology
		                        			;
		                        		
		                        			Hip
		                        			;
		                        		
		                        			Humans
		                        			;
		                        		
		                        			Incretins
		                        			;
		                        		
		                        			Osteoporosis
		                        			;
		                        		
		                        			Risk Assessment
		                        			
		                        		
		                        	
            
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