Fracture Risk in Middle-Aged and Older Patients With Inflammatory Bowel Disease: A Korean Nationwide Population-Based Cohort Study

Ji Min Lee; Kyungdo Han; Kang-Moon Lee; Jae-Seung Yun

doi:10.3346/jkms.2023.38.e275

Journal List > J Korean Med Sci > v.38(35) > 1516083840

Go to TopGo to Top Go to BottomGo to Bottom

TOOLS

Lee, Han, Lee, and Yun: Fracture Risk in Middle-Aged and Older Patients With Inflammatory Bowel Disease: A Korean Nationwide Population-Based Cohort Study

Original Article

Gastroenterology & Hepatology

Journal of Korean Medical Science 2023; 38(35): e275.

Published online: 17 August 2023

DOI: https://doi.org/10.3346/jkms.2023.38.e275

Fracture Risk in Middle-Aged and Older Patients With Inflammatory Bowel Disease: A Korean Nationwide Population-Based Cohort Study

Ji Min Lee¹

, Kyungdo Han²

, Kang-Moon Lee¹

, Jae-Seung Yun³

¹Division of Gastroenterology, Department of Internal Medicine, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.

²Department of Statistics and Actuarial Science, Soongsil University, Seoul, Korea.

³Division of Endocrinology, Department of Internal Medicine, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.

Address for Correspondence: Kyungdo Han, PhD. Department of Statistics and Actuarial Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 06978, Republic of Korea. hkd917@naver.com

Address for Correspondence: Kang-Moon Lee, MD. Division of Gastroenterology, Department of Internal Medicine, St. Vincent’s Hospital, College of Medicine, The Catholic University of Korea, 93 Jungbu-daero, Paldal-gu, Suwon 16247, Republic of Korea. drmaloman@catholic.ac.kr

Received 5 February 2023 Accepted 21 June 2023

The Korean Academy of Medical Sciences

https://creativecommons.org/licenses/by-nc/4.0/

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

Abstract

Background

Fracture risks and associated factors are poorly understood in middle-aged and older Asian populations with inflammatory bowel disease (IBD). Therefore, we investigated fracture risk and the effects of comorbidities and lifestyle habits on the risk of developing fractures in middle-aged and older Korean patients with IBD.

Methods

We conducted a nationwide population-based cohort study using data from the National Health Insurance Corporation Database. Patients with IBD who underwent the National Screening Program and were over 40 years of age were included in the study. We compared patients with age- and sex-matched controls. The incidence of fractures, including vertebral, hip, and other sites, was determined using claims data.

Results

The risk of total fractures and vertebral fractures was significantly higher in the IBD group (adjusted hazard ratio [HR], 1.31, 95% confidence interval [CI], 1.16–1.48; adjusted HR, 1.59, 95% CI, 1.33–1.92, respectively). Obesity, diabetes, hypertension, and lack of exercise were associated with increased fracture risk in patients with ulcerative colitis (UC). In contrast, the risk increases in patients with Crohn’s disease regardless of comorbidities and lifestyle preferences.

Conclusion

The risk of bone fracture, especially vertebral fracture, is high in middle-aged and older Korean patients with IBD. Obesity, diabetes, hypertension, and lack of exercise are all risk factors associated with bone fractures in patients with UC. These findings are helpful for clinicians to educate patients with IBD on bone health and raise awareness of bone fractures in patients with UC who have specific risk factors.

Graphical Abstract

Keywords: Fracture, Crohn’s Disease, Ulcerative Colitis, Risk, Inflammatory Bowel Disease

INTRODUCTION

Osteoporosis and bone fracture are linked to inflammatory bowel disease (IBD);1 2 3 4 several possible mechanisms can explain these. Corticosteroids, a mainstay treatment of active IBD, may affect bone loss and demineralization.5 A recent Swedish nationwide cohort study revealed that cumulative corticosteroid dosages in individuals with > 4,500 mg prednisolone equivalents increased hip and fracture risk in patients with IBD.6 Vitamin D, an important factor in calcium metabolism and healthy bone development, is commonly deficient in patients with IBD.7 Important bone metabolism and mineralization components may become unbalanced because of chronic inflammation.8 9

The aging of the population with IBD may increase the risk of concomitant conditions such as fractures.10 The mechanisms of fractures vary according to different age groups. In addition to skeletal variables, lifestyle and risk-taking behavior may influence fracture risk because children and adolescents are prone to fracture their bones while playing, participating in sports, or in accidents.11 12 In adults and older women, bone aging, such as frailty, changes in soft tissue composition, and reduced bone strength, may be more closely related to fractures.13 Previous data from Olmsted County, Minnesota, showed that younger individuals (aged 18–49 years) had a higher percentage of fracture of hands and feet and fewer fractures at conventional osteoporotic fracture sites, including the vertebra and hip, than older inhabitants (age ≥ 50 years).12 These differences may be observed in populations with IBD, where aging might contribute to the risk of fractures.

Recently, several epidemiologic studies reported that IBD increases the risk of fractures.6 14 However, most of these studies have primarily focused on corticosteroid use as a risk factor for fractures, and there is a lack of information regarding the fracture risks and associated factors related to comorbidities and lifestyle habits in IBD patients who are particularly vulnerable to age-related osteoporotic changes. Therefore, the objective of our study is to examine the fracture risk and factors associated with comorbidities and lifestyle in IBD patients who are susceptible to age-related osteoporotic changes. We investigate the fracture risks in middle-aged and older Korean patients with IBD and analyzes the impact of comorbidities and lifestyle habits on the risk of developing fractures using population-based data.

METHODS

Data source

In Korea, the National Health Insurance Service-National Health Information Database (NHIS-NHID) covers all claims data, including the International Classification of Disease (ICD) codes and rare intractable disease (RID) enrollment programs; researchers have access to information on treatment prescriptions and specifics of nationwide medical examinations of the entire population.15 16

This retrospective population-based cohort study used the NHIS-NHID. Approximately 97% of the enrolled Korean population, who are subjected to semi-required medical examinations every two years, are represented in the database. The NHIS database contains information on a person’s demographics, hospitalization, outpatient medical usage, drug use, medical interventions, and diagnoses denoted by the ICD, Tenth Revision (ICD-10) codes. Also, the national medical examinations included the data of lifestyle behavior questionnaire such as alcohol consumption, smoking, and exercise. The NHIS has established a program for enrolling patients with RIDs to improve medical reimbursement by lessening the economic strain of treating RIDs such as IBD. Trained physicians must determine if the disorders match the diagnostic standards for each RID to enroll individuals with RIDs in this program. A specific diagnostic code (V code), in addition to the ICD-10 code, is assigned upon registration in the RID program. Only patients with IBD who meet stringent comprehensive diagnostic requirements, such as imaging, histological, clinical, and endoscopic findings, are given the V code.

Study population

A total of 33,191 patients with IBD were included in this study. These patients were newly registered in the NHIS database with both ICD-10 and V codes from January 2010 to December 2016. To ensure the accuracy of the incidence rates (IRs), a washout period from 2002 to 2009 was implemented. During the process of identifying newly diagnosed IBD cases in 2010, patients who had been previously diagnosed with IBD between 2002 and 2009 were excluded from the analysis. ICD-10 K50 and V130 codes were used to identify patients with Crohn’s disease (CD), whereas the K51 and V131 codes were used to identify patients with ulcerative colitis (UC). Additionally, data were obtained from 14,265 patients with IBD who underwent an NHIS medical examination biannually between 2008 and 2014 and whose medical records were reviewed. Of these patients, 343 were eliminated because of missing values, such as laboratory test results. Finally, 9,855 individuals aged > 40 years were included in the study (Fig. 1). As a control group, 40,193 individuals without IBD were randomly selected and matched by age and sex at a 1:4 ratio. Participants in the study were monitored until fracture occurrence, censoring (such as death), or the final follow-up date (December 31, 2017), whichever occurred first. The mean follow-up period was 3.02 years with a standard deviation of 1.97 years. The median follow-up period was 2.77 years, with an interquartile range of 1.32–4.62 years.

Fig. 1

Flowchart showing the enrolment process for the study cohort.

IBD = inflammatory bowel disease, NHIC = National Health Insurance Corporation.

Outcome: fractures

ICD-10 codes for fractures were as follows: vertebral (S22.0, S22.1, S32.0, M48.4, and M48.5), hip (S72.0 and S72.1), and other fractures, including the upper arm (S42.0, S42.2, and S42.3), forearm (S52.5 and S52.6), and lower leg (S82.3, S82.5, and S82.6).14 17 18 Vertebral or other fractures were considered to have occurred when there were two or more outpatient visits during 12 months with the appropriate diagnosis codes. Hip fracture was defined as one hospitalization with an appropriate diagnostic code. ‘Other fractures’ was classified when individuals experienced at least one of the upper arm, forearm, or lower leg fractures.19

Covariates

A standardized self-reported questionnaire and information obtained from the medical examination were used to collect covariates for multivariate analysis. Demographic data including age, sex, place of residence, income level, cigarette smoking (never, former, and current), alcohol consumption (none, mild, and heavy), regular exercise (no, yes), body mass index (BMI), glomerular filtration rate (GFR), previous fracture history within five years in both the IBD and non-IBD groups were collected. We also collected information on comorbidities, including hypertension (defined as ICD-10 codes (I10–13, I15) with antihypertensive agents), diabetes mellitus (DM; defined as ICD-10 codes (E11–14) with antihyperglycemic agents), and dyslipidemia (defined as ICD-10 code (E78) with antihyperlipidemic agents), as described previously.20 21 Individuals whose alcohol consumption was < 30 g per day were defined as mild drinkers, and individuals whose alcohol consumption was > 30 g per day were defined as heavy drinkers.22 Regular exercise was based on the frequency and intensity of activity per week. Obesity was defined as a BMI cutoff of 25 kg/m².23 Chronic kidney disease (CKD) was defined based on the GFR, as estimated by the Modification of Diet in Renal Disease equation. The following GFR categories were recognized: ≥ 60, 30–60, and < 30 mL/min/1.73 m².

Statistical analysis

Baseline participant characteristics were calculated using numbers and percentages for categorical variables and means and standard deviations for continuous variables. The χ² test for categorical variables and the t-test for continuous variables were used to compare the characteristics of the groups. The IR was calculated based on the prevalence of the outcome per 1,000 person-years (PY) from the total fracture events and PY in each group.

Using Cox proportional hazards regression models, hazard ratios (HRs) and 95% confidence intervals (CIs) were computed relative to the reference to evaluate fracture risk in patients with IBD, and the association between fracture risk and comorbidities or lifestyle variables.

Subgroup analyses stratified by age, sex (male and female), obesity (< 25 and ≥ 25 kg/m²), cigarette smoking (current smoker or non-smoker), current alcohol consumption (none or heavy), regular exercise (no or yes), and comorbidities (diabetes, hypertension, and dyslipidemia) were conducted. Unadjusted HRs were assessed using Model 1 to evaluate the association between fracture risk and comorbidities or lifestyle habits. Adjusted HRs (aHRs) were calculated as Model 2 (adjusted for age and sex), Model 3 (adjusted for Model 2 + DM, hypertension, dyslipidemia, place of residence, income level, and previous fracture within five years), and Model 4 (adjusted for Model 3 + current smoking, alcohol consumption, regular exercise, BMI, and CKD). The Kaplan-Meier analysis and log-rank test were used to examine the cumulative incidence of fractures in the IBD and non-IBD groups. Statistical significance was set at P < 0.05. All statistical analyses were performed using the SAS software (version 9.3; SAS Institute, Cary, NC, USA). Two-sided P values< 0.05 were considered to indicate statistical significance for all analyses.

Ethics statement

The Catholic University of Korea’s Institutional Research Ethics Board reviewed and approved this study (VC19ZISI0300), waiving the need for informed consent because of the retrospective design and encrypted participant data.

RESULTS

Baseline characteristics of the study population

The baseline characteristics of the study participants are summarized in Table 1. The mean age was 54.5 years, and 61.4% were male in the IBD group. The IBD cohort had a lower mean age and a higher proportion of males than the non-IBD controls (P < 0.001, respectively). Compared with the non-IBD group, the IBD cohort had a reduced percentage of rural residents (P < 0.001) and individuals with income levels below 25% (P < 0.001). When compared with controls, the IBD cohort had a significantly decreased prevalence of DM (P < 0.001), hypertension (P < 0.001), and dyslipidemia (P < 0.001). There was no difference in the previous fracture rate within five years between the two groups.

Table 1

Baseline characteristics of the study participants

Characteristics		IBD			CD			UC
Characteristics		No (n = 40,193)	Yes (n = 9,855)	P	No (n = 6,786)	Yes (n = 1,509)	P	No (n = 33,407)	Yes (n = 8,346)	P
Age				< 0.001			0.024			0.009
	40–49	13,802 (34.34)	3,450 (35.01)		2,421 (35.68)	576 (38.17)		11,381 (34.07)	2,874 (34.44)
	50–59	13,278 (33.04)	3,380 (34.3)		2,030 (29.91)	471 (31.21)		11,248 (33.67)	2,909 (34.86)
	60–69	8,605 (21.41)	2,055 (20.85)		1,401 (20.65)	291 (19.28)		7,204 (21.56)	1,764 (21.14)
	≥ 70	4,508 (11.22)	970 (9.84)		934 (13.76)	171 (11.33)		3,574 (10.7)	799 (9.57)
	Mean ± SD	54.94 ± 10.4	54.52 ± 10.15	< 0.001	54.19 ± 10.57	53.97 ± 10.64	0.477	54.45 ± 9.84	54.33 ± 9.88	0.335
Male		23,790 (59.19)	6,048 (61.37)	< 0.001	3,697 (54.48)	839 (55.6)	0.429	20,093 (60.15)	5,209 (62.41)	< 0.001
Smoking				< 0.001			0.001			< 0.001
	Non-smoker	22,818 (56.77)	5,153 (52.29)		3,989 (58.78)	870 (57.65)		18,829 (56.36)	4,283 (51.32)
	Former smoker	8,145 (20.26)	3,438 (34.89)		1,262 (18.6)	338 (22.4)		6,883 (20.6)	3,100 (37.14)
	Current smoker	9,230 (22.96)	1,264 (12.83)		1,535 (22.62)	301 (19.95)		7,695 (23.03)	963 (11.54)
Alcohol consumption				< 0.001			< 0.001			< 0.001
	Non	21,745 (54.1)	5,736 (58.2)		3,777 (55.66)	988 (65.47)		17,968 (53.79)	4,748 (56.89)
	Mild	15,105 (37.58)	3,471 (35.22)		2,514 (37.05)	440 (29.16)		12,591 (37.69)	3,031 (36.32)
	Heavy	3,343 (8.32)	648 (6.58)		495 (7.29)	81 (5.37)		2,848 (8.53)	567 (6.79)
Regular exercise, yes		8,665 (21.56)	2,082 (21.13)	0.349	1,456 (21.46)	273 (18.09)	0.004	7,209 (21.58)	1,809 (21.68)	0.849
Lower quintile of yearly income		10,115 (25.17)	2,472 (25.08)	< 0.001	1,733 (25.54)	389 (25.78)	0.846	8,382 (25.09)	2,083 (24.96)	0.803
Residency, rural		4,208 (10.47)	908 (9.21)	< 0.001	625 (9.21)	138 (9.15)	0.937	3,583 (10.73)	770 (9.23)	< 0.001
BMI, kg/m²		24.06 ± 3.1	23.49 ± 2.98	< 0.001	24.1 ± 3.21	22.93 ± 3.22	< 0.001	24.08 ± 3.13	23.57 ± 2.97	< 0.001
	Obesity^a	14,263 (35.49)	2,856 (29.07)	< 0.001	2,382 (35.1)	369 (24.45)	< 0.001	11,881 (35.56)	2,496 (29.91)	< 0.001
Hypertension		12,675 (31.54)	2,779 (28.2)	< 0.001	2,107 (31.05)	418 (27.7)	< 0.001	10,568 (31.63)	2,361 (28.29)	< 0.001
DM		5,249 (13.06)	971 (9.85)	< 0.001	831 (12.25)	160 (10.6)	0.008	4,418 (13.22)	811 (9.72)	< 0.001
Dyslipidemia		8,733 (21.73)	1,756 (17.82)	< 0.001	1,504 (22.16)	270 (17.89)	< 0.001	7,229 (21.64)	1,486 (17.8)	< 0.001
GFR, mL/min/1.73 m²		89 ± 43.56	90.95 ± 51.17	< 0.001	88.45 ± 25.62	91.43 ± 37.7	< 0.001	88.6 ± 25.15	89.51 ± 27.59	0.005
Previous fracture with 5 yr		1,471 (3.66)	346 (3.51)	0.479	249 (3.67)	66 (4.37)	0.195	1,222 (3.66)	280 (3.35)	0.184

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

BMI = body mass index, CD = Crohn’s disease, DM = diabetes mellitus, GFR = glomerular filtration rate, IBD = inflammatory bowel disease, SD = standard deviation, UC = ulcerative colitis.

^aObesity was defined with BMI cutoff of 25 kg/m².

Risk of fractures in patients with IBD

Despite adjustment for age, sex, place of residence, income level, history of the previous fracture within five years, comorbidities like DM, hypertension, and dyslipidemia, and lifestyle habits such as smoking, alcohol consumption, and regular exercise, the HR indicated that the risk of total fracture was significantly higher in the IBD group than that in the non-IBD group. Similar trends were observed in the UC and CD cohorts (Table 2). Additionally, the cumulative incidence of fractures in the IBD group was significantly higher than in the non-IBD group (P = 0.008, Fig. 2A).

Table 2

Risk of fracture in patients with IBD

Characteristics			Total No.	Fracture events	Duration (PY)	IR (per 1,000 PY)	HR (95% CI)
Characteristics			Total No.	Fracture events	Duration (PY)	IR (per 1,000 PY)	Model 1	Model 2	Model 3	Model 4
Total fracture
	IBD
		Control	40,193	1,160	118,611.74	9.780	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	9,855	333	28,851.15	11.542	1.18 (1.04–1.33)	1.29 (1.14–1.46)	1.31 (1.16–1.48)	1.31 (1.16–1.48)
	CD
		Control	6,786	204	19,559.68	10.430	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	1,509	74	4,213.82	17.561	1.68 (1.28–2.19)	1.93 (1.48–2.52)	1.87 (1.43–2.44)	1.92 (1.47–2.52)
	UC
		Control	33,407	956	99,052.06	9.652	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	8,346	259	24,637.33	10.513	1.09 (0.95–1.25)	1.17 (1.02–1.34)	1.20 (1.04–1.37)	1.19 (1.03–1.37)
Other fracture
	IBD
		Control	40,193	612	118,611.74	5.160	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	9,855	155	28,851.15	5.372	1.04 (0.87–1.24)	1.10 (0.93–1.32)	1.12 (0.94–1.33)	1.12 (0.94–1.34)
	CD
		Control	6,786	110	19,559.68	5.624	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	1,509	33	4,213.82	7.831	1.39 (0.94–2.05)	1.50 (1.02–2.22)	1.49 (1.01–2.20)	1.53 (1.03–2.28)
	UC
		Control	33,407	502	99,052.06	5.068	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	8,346	122	24,637.33	4.952	0.98 (0.80–1.19)	1.03 (0.84–1.25)	1.04 (0.85–1.27)	1.04 (0.85–1.27)
Hip fracture
	IBD
		Control	40,193	64	118,611.74	0.540	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	9,855	19	28,851.15	0.659	1.22 (0.73–2.04)	1.39 (0.83–2.33)	1.43 (0.86–2.39)	1.36 (0.81–2.28)
	CD
		Control	6,786	12	19,559.68	0.610	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	1,509	3	4,213.82	0.712	1.16 (0.33–4.11)	1.51 (0.42–5.41)	1.35 (0.37–4.84)	1.14 (0.31–4.21)
	UC
		Control	33,407	52	99,052.06	0.525	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	8,346	16	24,637.33	0.649	1.24 (0.71–2.17)	1.36 (0.78–2.38)	1.41 (0.80–2.48)	1.34 (0.76–2.37)
Vertebral fracture
	IBD
		Control	40,193	471	118,611.74	3.971	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	9,855	157	28,851.15	5.441	1.37 (1.14–1.64)	1.55 (1.29–1.86)	1.58 (1.32–1.90)	1.59(1.33–1.92)
	CD
		Control	6,786	80	19,559.68	4.090	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	1,509	37	4,213.82	8.781	2.14 (1.45–3.15)	2.59 (1.75–3.82)	2.50 (1.69–3.70)	2.60 (1.74–3.88)
	UC
		Control	33,407	391	99,052.06	3.947	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)	1.00 (Ref.)
		Case	8,346	120	24,637.33	4.871	1.23 (1.01–1.51)	1.37 (1.11–1.68)	1.41 (1.15–1.74)	1.42 (1.15–1.75)

Model 1: unadjusted analysis. Model 2: adjusted for age and sex. Model 3: adjusted for Model 2 + place of residence, income level, diabetes mellitus, hypertension, dyslipidemia and previous fracture within 5 years. Model 4: adjusted for Model 3 + body mass index, chronic kidney disease, current smoking, alcohol consumption and regular exercise.

CD = Crohn’s disease, CI = confidence interval, HR = hazard ratio, IBD = inflammatory bowel disease, IR = incidence rate, PY = person-years, Ref. = reference, UC = ulcerative colitis.

Fig. 2

Kaplan-Meier plots show the cumulative incidence of fractures in patients with IBD, CD and UC. (A) Total fractures. (B) Vertebral fractures. (C) Hip fractures. (D) Other fractures.

IBD = inflammatory bowel disease, CD = Crohn’s disease, UC = ulcerative colitis.

According to the type of fractures, the risk of vertebral fractures was significantly higher in patients with IBD, CD, and UC (aHR, 1.59, 95% CI, 1.33–1.92; aHR, 2.6, 95% CI, 1.74–3.88 and aHR, 1.42, 95% CI, 1.15–1.75 in Model 4, respectively). The risk of other fractures among CD patients, but not UC patients, was higher than that in the control group (aHR, 1.53, 95% CI, 1.03–2.28). IBD, CD, and UC were not associated with an increased risk of hip fracture (Table 2). The cumulative incidence of hip and other fractures in the IBD group was not significantly different from that in the control group (P = 0.656 and 0.444, respectively) (Fig. 2B and C). However, the cumulative incidence of vertebral fractures in IBD was significantly higher than in the non-IBD group (P = 0.001) (Fig. 2D).

Subgroup analysis

We examined the differences in the risk of fracture among patients with IBD, CD, and UC after adjusting for age, sex, place of residence, income level, history of prior fracture within five years, comorbidities like DM, hypertension, dyslipidemia, lifestyle habits such as smoking, alcohol consumption, and regular exercise (Table 3). The impact of IBD on the occurrence of fractures was significant in patients aged between 70 and 80 years (HR, 1.65) and above 80 years (HR, 1.82) and with comorbidities such as obesity (HR, 1.45), diabetes (HR, 1.43), hypertension (HR, 1.53), and dyslipidemia (HR, 1.42). Besides, the impact of UC on the development of fractures was more prominent in patients aged 70–80 years (HR, 1.44), with comorbidities such as obesity (HR, 1.32), diabetes (HR, 1.58), hypertension (HR, 1.35), and no regular exercise (HR, 1.21). In contrast, fracture risk tended to increase regardless of age, sex, comorbidities, and lifestyle habits in patients with CD.

Table 3

Subgroup analysis of risk for fracture in patients with inflammatory bowel disease

Characteristics			IBD					CD					UC
Characteristics			No.	Fx	Duration (PY)	IR (per 1,000 PY)	HR (95% CI)	No.	Fx	Duration (PY)	IR (per 1,000 PY)	HR (95% CI)	No.	Fx	Duration (PY)	IR (per 1,000 PY)	HR (95% CI)
Age, yr
	40–49
		Control	13,802	119	42,134	2.824	1.00 (Ref.)	2,421	25	7,400	3.378	1.00 (Ref.)	11,381	94	34,734	2.706	1.00 (Ref.)
		Case	3,450	28	10,447	2.680	1.01 (0.66–1.53)	576	5	1,758	2.844	1.01 (0.37–2.71)	2,874	23	8,689	2.647	0.98 (0.62–1.57)
	50–59
		Control	13,278	290	39,762	7.293	1.00 (Ref.)	2,030	43	5,978	7.193	1.00 (Ref.)	11,248	247	33,783	7.311	1.00 (Ref.)
		Case	3,380	88	10,167	8.656	1.21 (0.95–1.54)	471	17	1,363	12.470	1.91 (1.07–3.04)	2,909	71	8,804	8.065	1.10 (0.84–1.44)
	60–69
		Control	8,605	386	24,548	15.720	1.00 (Ref.)	1,401	60	3,800	15.790	1.00 (Ref.)	7,204	326	20,748	15.710	1.00 (Ref.)
		Case	2,055	104	5,771	18.020	1.15 (0.92–1.43)	291	23	761.6	30.200	1.71 (1.05–2.79)	1,764	81	5,009	16.170	1.04 (0.81–1.33)
	70–79
		Control	3,928	300	10,920	27.470	1.00 (Ref.)	794	67	2,107	31.800	1.00 (Ref.)	3,134	233	8,813	26.440	1.00 (Ref.)
		Case	837	93	2,223	41.840	1.65 (1.30–2.08)	142	25	289	86.520	2.75 (1.70–4.44)	695	68	1,934	35.160	1.44 (1.10–1.90)
	≥ 80
		Control	580	65	1,248	52.090	1.00 (Ref.)	140	9	274.7	32.760	1.00 (Ref.)	440	56	973	57.550	1.00 (Ref.)
		Case	133	20	244	81.970	1.82 (1.08–3.09)	29	4	41.81	95.670	2.14 (0.52–8.86)	104	16	202.2	79.130	1.77 (0.97–3.23)
Sex
	Male
		Control	23,790	444	70,243	6.321	1.00 (Ref.)	3,697	57	10,750	5.302	1.00 (Ref.)	20,093	387	59,493	6.505	1.00 (Ref.)
		Case	6,048	135	17,832	7.571	1.24 (1.02–1.52)	839	20	2,376	8.416	1.84 (1.09–3.12)	5,209	115	15,456	7.441	1.17 (0.95–1.45)
	Female
		Control	16,403	716	48,369	14.800	1.00 (Ref.)	3,089	147	8,810	16.690	1.00 (Ref.)	13,314	569	39,559	14.380	1.00 (Ref.)
		Case	3,807	198	11,019	17.970	1.34 (1.14–1.57)	670	54	1,837	29.390	1.98 (1.44–2.72)	3,137	144	9,182	15.680	1.18 (0.98–1.42)
Obesity
	No
		Control	25,930	778	77,211	10.080	1.00 (Ref.)	4,404	136	12,777	10.640	1.00 (Ref.)	21,526	642	64,434	9.964	1.00 (Ref.)
		Case	6,990	236	20,493	11.520	1.26 (1.09–1.46)	1,140	56	3,216	17.410	1.86 (1.35–2.54)	5,850	180	17,277	10.420	1.13 (0.96–1.34)
	Yes
		Control	14,263	382	41,401	9.227	1.00 (Ref.)	2,382	68	6,782	10.030	1.00 (Ref.)	11,881	314	34,619	9.070	1.00 (Ref.)
		Case	2,865	97	8,358	11.610	1.45 (1.16–1.82)	369	18	997.4	18.050	2.20 (1.30–3.73)	2,496	79	7,361	10.730	1.32 (1.03–1.70)
DM
	No
		Control	34,944	971	102,843	9.442	1.00 (Ref.)	5,955	162	17,136	9.454	1.00 (Ref.)	28,989	809	85,707	9.439	1.00 (Ref.)
		Case	8,884	286	25,863	11.060	1.29 (1.13–1.48)	1,349	64	3,727	17.170	2.21 (1.64–2.97)	7,535	222	22,136	10.030	1.14 (0.98–1.32)
	Yes
		Control	5,249	189	15,769	11.990	1.00 (Ref.)	831	42	2,424	17.330	1.00 (Ref.)	4,418	147	13,345	11.020	1.00 (Ref.)
		Case	971	47	2,988	15.730	1.43 (1.03–1.97)	160	10	486.4	20.560	1.16 (0.57–2.37)	811	37	2,502	14.790	1.58 (1.10–2.29)
Hypertension
	No
		Control	27,518	642	78,023	8.228	1.00 (Ref.)	4,679	117	12,929	9.050	1.00 (Ref.)	22,839	525	65,094	8.065	1.00 (Ref.)
		Case	7,076	175	19,998	8.751	1.16 (0.98–1.37)	1,091	36	3,011	11.960	1.55 (1.05–2.27)	5,985	139	16,987	8.183	1.07 (0.89–1.30)
	Yes
		Control	12,675	518	40,589	12.760	1.00 (Ref.)	2,107	87	6,631	13.120	1.00 (Ref.)	10,568	431	33,958	12.690	1.00 (Ref.)
		Case	2,779	158	8,853	17.850	1.53 (1.28–1.83)	418	38	1,203	31.590	2.47 (1.67–3.64)	2,361	120	7,650	15.690	1.35 (1.10–1.66)
Dyslipidemia
	No
		Control	31,460	861	91,104	9.451	1.00 (Ref.)	5,282	145	14,946	9.702	1.00 (Ref.)	26,178	716	76,158	9.402	1.00 (Ref.)
		Case	8,099	255	23,326	10.930	1.28 (1.11–1.47)	1,239	52	3,431	15.160	1.82 (1.31–2.52)	6,860	203	19,895	10.200	1.17 (1.00–1.37)
	Yes
		Control	8,733	299	27,508	10.870	1.00 (Ref.)	1,504	59	4,614	12.790	1.00 (Ref.)	7,229	240	22,894	10.480	1.00 (Ref.)
		Case	1,756	78	5,525	14.120	1.42 (1.10–1.83)	270	22	782.8	28.100	2.26 (1.37–3.75)	1,486	56	4,742	11.810	1.25 (0.93–1.68)
Alcohol consumption
	No
		Control	36,850	1,103	108,687	10.150	1.00 (Ref.)	6,291	198	18,062	10.960	1.00 (Ref.)	30,559	905	90,626	9.986	1.00 (Ref.)
		Case	9,207	320	26,975	11.860	1.31 (1.16–1.49)	1,428	71	3,972	17.870	1.89 (1.43–2.49)	7,779	249	23,002	10.830	1.19 (1.04–1.38)
	Yes
		Control	3,343	57	9,924	5.743	1.00 (Ref.)	495	6	1,498	4.005	1.00 (Ref.)	2,848	51	8,426	6.053	1.00 (Ref.)
		Case	648	13	1,876	6.928	1.30 (0.70–2.41)	81	3	241.5	12.420	3.3 (0.70–15.64)	567	10	1,635	6.116	1.13 (0.56–2.26)
Smoking
	No
		Control	30,963	993	90,831	10.930	1.00 (Ref.)	5,251	176	14,926	11.790	1.00 (Ref.)	25,712	817	75,905	10.760	1.00 (Ref.)
		Case	8,591	305	25,082	12.160	1.335 (1.173–1.520)	1,201	62	3,301	18.780	1.854 (1.379–2.491)	7,390	243	21,781	11.160	1.236 (1.070–1.429)
	Current
		Control	9,230	167	27,780	6.011	1.00 (Ref.)	1,535	28	4,633	6.043	1.00 (Ref.)	7,695	139	23,147	6.005	1.00 (Ref.)
		Case	1,264	28	3,769	7.429	1.172 (0.783–1.755)	308	12	912.5	13.150	2.511 (1.240–5.084)	956	16	2,857	5.601	0.846 (0.501–1.428)
Regular exercise
	No
		Control	31,528	948	93,133	10.180	1.00 (Ref.)	5,330	171	15,408	11.100	1.00 (Ref.)	26,198	777	77,725	9.997	1.00 (Ref.)
		Case	7,773	269	22,814	11.790	1.318 (1.149–1.512)	1,236	60	3,479	17.250	1.830 (1.356–2.470)	6,537	209	19,335	10.810	1.211 (1.037–1.414)
	Yes
		Control	8,665	212	25,479	8.321	1.00 (Ref.)	1,456	33	4,151	7.949	1.00 (Ref.)	7,209	179	21,328	8.393	1.00 (Ref.)
		Case	2,082	64	6,037	10.600	1.271 (0.956–1.691)	273	14	735.1	19.050	2.455 (1.279–4.710)	1,809	50	5,302	9.430	1.092 (0.793–1.504)

CD = Crohn’s disease, CI = confidence interval, HR = hazard ratio, IBD = inflammatory bowel disease, Fx = fracture events, IR = incidence rate, PY = person-years, Ref. = reference, UC = ulcerative colitis, DM = diabetes mellitus.

DISCUSSION

We found that the total and vertebral fracture risks in middle-aged and older Korean patients with IBD were significantly higher than in non-IBD individuals. To the best of our knowledge, this is the first nationwide cohort study to reveal the effects of comorbidities, lifestyle habits, and fracture risks in middle-aged and older populations with IBD. Interestingly, the fracture risk in CD increased regardless of age, sex, comorbidities, and lifestyle habits. At the same time, obesity, diabetes, hypertension, and no regular exercise were associated with increased fracture risk in UC.

Recently, several related studies have been published. A Swedish nationwide study revealed that hip and any fracture risks in an adult IBD group were higher than those in a non-IBD group (HR, 1.4 and 1.18, respectively) and were significantly associated with corticosteroid use.6 Similarly, a Korean nationwide study reported that vertebral and hip fracture risks in an IBD group were higher than in a non-IBD group (HR, 1.24), regardless of corticosteroid use.14 The results of both studies were similar to those of our study in terms of increasing fracture risks in IBD. Still, the studies included all IBD patients regardless of age, did not consider lifestyle habit and focused on corticosteroid use as a risk factor. Unlike previous studies, we included only middle-aged and older patients who could undergo osteoporotic changes and consider lifestyle behavior and comorbidities.

Our studies showed that vertebral fracture risk significantly increased in patients with IBD, UC, and CD. Long-term steroid use and bone composition may be associated with this. The ratio of cortical to the trabecular bone in the vertebrae is 25:75. In the femoral head, this proportion was 50:50.24 Riggs et al.25 reported that trabecular volumetric bone mineral density begins to decrease before middle age and proceeds linearly in both sexes, most prominently at the spine. In contrast, cortical volumetric bone mineral density decreases slightly with aging at the femoral neck. Corticosteroid use is a well-known risk factor for osteoporosis and bone fracture. Patients with IBD are often treated long-term with steroids. Glucocorticoid exposure was reported to be associated with a 60% increased risk of hip fracture and a 160% increased risk of vertebral fracture.26

Our study showed an increased risk of vertebral fractures rather than hip fractures, which differs from other studies, and this may be due to differences in the study population. Our study targeted patients aged 40 and above, while previous studies included all patients regardless of age. The risk of vertebral fractures in individuals over the age of 40 is generally related to osteoporosis, which is a condition that causes a decrease in bone density. A decrease in bone density can weaken the bones and increase the likelihood of vertebral fractures.27 On the other hand, the risk of hip fractures is not strongly related to osteoporosis. Instead, the risk of hip fractures is primarily associated with changes in the soft tissues that occur with age. Soft tissues play a role in supporting and stabilizing the joint, so changes in soft tissues can weaken the stability of the hip joint and increase the risk of hip fractures.27 28

Vertebral fractures can cause back pain, worsening spinal deformity, limited mobility, and diminished pulmonary function, severely limiting independence and occasionally requiring hospitalization.29 30 31 Therefore, we must interpret our results regarding the increased risk of vertebral fractures in IBD with caution.

Interestingly, bone fractures in patients with UC are associated with obesity, diabetes, hypertension, and lack of exercise; but further research is needed to uncover the related mechanisms. Previous studies have revealed that obesity, diabetes, hypertension, and exercise are associated with osteoporosis and fractures. The impact of several adipokines and cytokines released by adipose tissue, including leptin, resistin, adiponectin, interleukin 6, and tumor necrosis factor-alpha, on bone could be the cause of osteoporosis in obesity.32 33 Systemic inflammation, advanced glycation end-product accumulation, and reactive oxygen species generation are all significantly altered in type 2 diabetes. These systemic alterations may have a negative impact on the bone remodeling cycle.34 Important links exist between changes in calcium metabolism and hypertension, including increased calcium loss, compensatory parathyroid gland activation, and increased calcium transit from bones. Deterioration of calcium homeostasis in long-term hypertension may lead to age-related osteoporosis and fracture.35 The risk of osteoporotic fracture being decreased by exercise is becoming more widely accepted since it can increase muscle strength and postural stability.36 There is still no clear evidence in patients with UC that there might be synergistic mechanisms for these factors to cause bone fracture. However, these findings are relevant because our study used large-scale population data. Therefore, in middle-aged and older patients with UC, we could cautiously assume that managing obesity, diabetes, hypertension, and exercise might help prevent fractures.

The major strengths of our study are as follows: 1) this is the first study to analyze the effects of comorbidities, lifestyle habits, and risk of fracture in the middle-aged and older population with IBD using a nationwide, population-based cohort; 2) we could use the data and information from in-depth surveys and laboratory results in the national checkup program; therefore, we performed the analysis using a large number of variables. However, our study also had some limitations, as follows: 1) our study did not consider drug use such as corticosteroid, immunomodulators and biologics. In our study, we found a higher risk of fractures in CD compared to UC. This may be potentially associated with the usage of steroids. It is well-known traditionally that steroid usage is more frequent in CD than in UC.37 However, due to limitations in our data, we were unable to analyze the impact of steroid usage; 2) because we used claims data, the definition of fracture could have caused bias; 3) we could not determine the cause of bone fracture; 4) the follow-up period in our study was relatively short; 5) there is a possibility that hip fractures may have been underestimated in this study. Because, vertebral fractures are often asymptomatic and may not be clinically diagnosed without imaging, while hip fractures usually present with more symptoms and are more likely to be clinically diagnosed; and 6) there are significant differences in age and gender between patients with IBD and the control group, despite age and gender matching. During the selection process of the final study participants, it was observed that the age and gender ratios were not maintained despite efforts to match for age and gender. Therefore, in our study, we included age and gender as covariates in the analysis to account for these potential confounding factors.

In conclusion, the risk of bone fracture, especially vertebral fracture, is increasing in middle-aged and older Korean patients with IBD. Obesity, diabetes, hypertension, and lack of exercise have increased the risk of bone fracture in UC but not in CD. These findings may be helpful for clinicians to educate patients with IBD on bone health and raise awareness of bone fractures in patients with UC who have specific risk factors.

Notes

Funding: This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education (2020R1I1A1A01070322).

Disclosure: This study used National Health Insurance Service (NHIS)-National Health Information Database (NHID) (NHIS-2022-1-072) made by NHIS. The authors declare no conflicts of interest with NHIS.

Author Contributions:

Conceptualization: Lee JM, Han K, Lee KM, Yun JS.
Data curation: Han K, Yun JS.
Formal analysis: Han K.
Funding acquisition: Lee JM.
Investigation: Lee JM, Lee KM, Yun JS.
Methodology: Lee JM, Han K, Lee KM, Yun JS.
Resources: Lee JM, Han K.
Supervision: Han K, Lee KM, Yun JS.
Validation: Han K.
Visualization: Lee JM, Han K, Lee KM.
Writing - original draft: Lee JM.
Writing - review & editing: Lee JM, Lee KM, Yun JS.

References

1. Card T, West J, Hubbard R, Logan RF. Hip fractures in patients with inflammatory bowel disease and their relationship to corticosteroid use: a population based cohort study. Gut. 2004; 53(2):251–255. PMID: 14724159.

2. Vestergaard P, Mosekilde L. Fracture risk in patients with celiac disease, Crohn’s disease, and ulcerative colitis: a nationwide follow-up study of 16,416 patients in Denmark. Am J Epidemiol. 2002; 156(1):1–10. PMID: 12076883.

3. van Staa TP, Cooper C, Brusse LS, Leufkens H, Javaid MK, Arden NK. Inflammatory bowel disease and the risk of fracture. Gastroenterology. 2003; 125(6):1591–1597. PMID: 14724810.

4. Kappelman MD, Galanko JA, Porter CQ, Sandler RS. Risk of diagnosed fractures in children with inflammatory bowel diseases. Inflamm Bowel Dis. 2011; 17(5):1125–1130. PMID: 20872833.

5. van Staa TP, Leufkens HG, Cooper C. The epidemiology of corticosteroid-induced osteoporosis: a meta-analysis. Osteoporos Int. 2002; 13(10):777–787. PMID: 12378366.

6. Ludvigsson JF, Mahl M, Sachs MC, Björk J, Michaelsson K, Ekbom A, et al. Fracture risk in patients with inflammatory bowel disease: a nationwide population-based cohort study from 1964 to 2014. Am J Gastroenterol. 2019; 114(2):291–304. PMID: 30730858.

7. Levin AD, Wadhera V, Leach ST, Woodhead HJ, Lemberg DA, Mendoza-Cruz AC, et al. Vitamin D deficiency in children with inflammatory bowel disease. Dig Dis Sci. 2011; 56(3):830–836. PMID: 21222159.

8. Metzger CE, Narayanan A, Zawieja DC, Bloomfield SA. Inflammatory bowel disease in a rodent model alters osteocyte protein levels controlling bone turnover. J Bone Miner Res. 2017; 32(4):802–813. PMID: 27796050.

9. Manolagas SC, Parfitt AM. What old means to bone. Trends Endocrinol Metab. 2010; 21(6):369–374. PMID: 20223679.

10. Segal JP, Htet HM, Limdi J, Hayee B. How to manage IBD in the ‘elderly’. Frontline Gastroenterol. 2020; 11(6):468–477. PMID: 33101625.

11. Goulding A. Risk factors for fractures in normally active children and adolescents. Med Sport Sci. 2007; 51:102–120. PMID: 17505122.

12. Farr JN, Melton LJ 3rd, Achenbach SJ, Atkinson EJ, Khosla S, Amin S. Fracture incidence and characteristics in young adults aged 18 to 49 years: a population-based study. J Bone Miner Res. 2017; 32(12):2347–2354. PMID: 28972667.

13. Wu F, Mason B, Horne A, Ames R, Clearwater J, Liu M, et al. Fractures between the ages of 20 and 50 years increase women’s risk of subsequent fractures. Arch Intern Med. 2002; 162(1):33–36. PMID: 11784217.

14. Ahn HJ, Kim YJ, Lee HS, Park JH, Hwang SW, Yang DH, et al. High risk of fractures within 7 years of diagnosis in Asian patients with inflammatory bowel diseases. Clin Gastroenterol Hepatol. 2022; 20(5):e1022–e1039. PMID: 34216823.

15. Lee J, Lee JS, Park SH, Shin SA, Kim K. Cohort profile: the National Health Insurance Service-National Sample Cohort (NHIS-NSC), South Korea. Int J Epidemiol. 2017; 46(2):e15. PMID: 26822938.

16. Song SO, Jung CH, Song YD, Park CY, Kwon HS, Cha BS, et al. Background and data configuration process of a nationwide population-based study using the Korean National Health Insurance system. Diabetes Metab J. 2014; 38(5):395–403. PMID: 25349827.

17. Lix LM, Azimaee M, Osman BA, Caetano P, Morin S, Metge C, et al. Osteoporosis-related fracture case definitions for population-based administrative data. BMC Public Health. 2012; 12(1):301. PMID: 22537071.

18. Jeong SM, Shin DW, Han K, Jung JH, Chun S, Jung HW, et al. Timed up-and-go test is a useful predictor of fracture incidence. Bone. 2019; 127:474–481. PMID: 31323429.

19. Yoo JE, Yoon JW, Park HE, Han K, Shin DW. Blood pressure variability and the risk of fracture: a nationwide cohort study. J Clin Endocrinol Metab. 2022; 107(4):e1488–e1500. PMID: 34850029.

20. Park S, Chun J, Han KD, Soh H, Kang EA, Lee HJ, et al. Dose-response relationship between cigarette smoking and risk of ulcerative colitis: a nationwide population-based study. J Gastroenterol. 2019; 54(10):881–890. PMID: 31093771.

21. Soh H, Chun J, Han K, Park S, Choi G, Kim J, et al. Increased risk of herpes zoster in young and metabolically healthy patients with inflammatory bowel disease: a nationwide population-based study. Gut Liver. 2019; 13(3):333–341. PMID: 30602222.

22. Lee JM, Lee KM, Kim DB, Ko SH, Park YG. Colorectal cancer risks according to sex differences in patients with type II diabetes mellitus: a Korean nationwide population-based cohort study. Clin Transl Gastroenterol. 2019; 10(10):e00090. PMID: 31651449.

23. Yang HK, Han K, Kwon HS, Park YM, Cho JH, Yoon KH, et al. Obesity, metabolic health, and mortality in adults: a nationwide population-based study in Korea. Sci Rep. 2016; 6(1):30329. PMID: 27445194.

24. Alberti KG, Zimmet P, Shaw J. Metabolic syndrome--a new world-wide definition. A consensus statement from the International Diabetes Federation. Diabet Med. 2006; 23(5):469–480. PMID: 16681555.

25. Riggs BL, Melton Iii LJ 3rd, Robb RA, Camp JJ, Atkinson EJ, Peterson JM, et al. Population-based study of age and sex differences in bone volumetric density, size, geometry, and structure at different skeletal sites. J Bone Miner Res. 2004; 19(12):1945–1954. PMID: 15537436.

26. Van Staa TP, Leufkens HG, Abenhaim L, Zhang B, Cooper C. Use of oral corticosteroids and risk of fractures. J Bone Miner Res. 2000; 15(6):993–1000. PMID: 10841167.

27. Chen H, Zhou X, Fujita H, Onozuka M, Kubo KY. Age-related changes in trabecular and cortical bone microstructure. Int J Endocrinol. 2013; 2013:213234. PMID: 23573086.

28. Bouxsein ML, Szulc P, Munoz F, Thrall E, Sornay-Rendu E, Delmas PD. Contribution of trochanteric soft tissues to fall force estimates, the factor of risk, and prediction of hip fracture risk. J Bone Miner Res. 2007; 22(6):825–831. PMID: 17352651.

29. Sànchez-Riera L, Wilson N. Fragility fractures & their impact on older people. Best Pract Res Clin Rheumatol. 2017; 31(2):169–191. PMID: 29224695.

30. Kanis JA, Oden A, Johnell O, De Laet C, Jonsson B. Excess mortality after hospitalisation for vertebral fracture. Osteoporos Int. 2004; 15(2):108–112. PMID: 14598026.

31. Ballane G, Cauley JA, Luckey MM, El-Hajj Fuleihan G. Worldwide prevalence and incidence of osteoporotic vertebral fractures. Osteoporos Int. 2017; 28(5):1531–1542. PMID: 28168409.

32. Greco EA, Fornari R, Rossi F, Santiemma V, Prossomariti G, Annoscia C, et al. Is obesity protective for osteoporosis? Evaluation of bone mineral density in individuals with high body mass index. Int J Clin Pract. 2010; 64(6):817–820. PMID: 20518955.

33. Scherer PE. Adipose tissue: from lipid storage compartment to endocrine organ. Diabetes. 2006; 55(6):1537–1545. PMID: 16731815.

34. Moseley KF. Type 2 diabetes and bone fractures. Curr Opin Endocrinol Diabetes Obes. 2012; 19(2):128–135. PMID: 22262002.

35. Cappuccio FP, Meilahn E, Zmuda JM, Cauley JA. Study of Osteoporotic Fractures Research Group. High blood pressure and bone-mineral loss in elderly white women: a prospective study. Lancet. 1999; 354(9183):971–975. PMID: 10501357.

36. Bassey EJ. Exercise for prevention of osteoporotic fracture. Age Ageing. 2001; 30(Suppl 4):29–31. PMID: 11769785.

37. Faubion WA Jr, Loftus EV Jr, Harmsen WS, Zinsmeister AR, Sandborn WJ. The natural history of corticosteroid therapy for inflammatory bowel disease: a population-based study. Gastroenterology. 2001; 121(2):255–260. PMID: 11487534.

TOOLS

Similar articles