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Abstract Number: 1244

Low Bone Mineral Density In African-American Males May Be More Prevalent Than Previously Reported and Exhibits Association With Low BMI But Not Older Age – Results Of a Retrospective Cohort Analysis

Khush Aujla1 and Vikas Majithia2, 1Division of Rheumatology, University of Mississippi School of Medicine, Jackson, MS, 2Div of Rheumatology, University of Mississippi Medical Center, Jackson, MS

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: Body mass and osteoporosis

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Session Information

Title: Osteoporosis and Metabolic Bone Disease: Clinical Aspects and Pathogenesis

Session Type: Abstract Submissions (ACR)

Background/Purpose: Osteoporosis (OP) in Males is prevalent and frequently under-recognized. There are a number of known demographic factors such as age, race and BMI as well as secondary causes of low bone mineral density (BMD) i.e. osteopenia and OP. The effect of these on the prevalence of low BMD has not been well quantified. This study aims to describe the prevalence of the demographic factors and SC in men with low BMD and also assess their impact on the prevalence.
Methods: Retrospective chart review of men who underwent DEXA scan performed at UMC from 2005- 2012 was done. Data regarding BMD, demographics i.e. age, race, height, weight, BMI, secondary medical causes, medications, social factors such as smoking and alcohol use was abstracted, tabulated and analyzed using STATA software. Statistical significance was assessed using T-test and Odds ratio as appropriate.

Results: A total of 585 charts were analyzed. There were 410 whites (W),  175 African-Americans (AA). 148 patients had normal BMD. Low bone density was prevalent and seen in 437 patients (74.7%). Amongst these 143 (24.4%) had T-score < -2.5 (osteoporosis) and 294 (50.25%) had T-score > – 2.5 and <-1.0 (osteopenia) BMD. The prevalence results are presented in the table with significant differences highlighted.

NORMAL

BONE DENSITY

OSTEOPOROSIS

(T-Score <-2.5)

DEMOGRAPHICS

AGE (mean)

57.59 years

59.34 years

p-NS

AA

55.33

56.04

p-NS

Whites

62.80

62.64

p-NS

BMI (mean)

31.74

26.07*

*p< 0.001

AA

33.18

26.63*

*p< 0.001

Whites

30.30

25.51*

*p< 0.001

SECONDARY MEDICAL DISORDERS (%)

ANY Disorder

69.69 %

80.32 %

p= 0.11

Thyroid Disorders

13.63 %

16.39%

p-NS

Hyperparathyroidism

4.54 %

3.27 %

p-NS

Diabetes

28.78 %

16.39%

p-NS

Asthma/COPD

6.75%

 16.1 %

*p<0.05

Rheumatoid Arthritis

10.6 %

16.66 %

p-NS

Other Connective tissue Disorders

7.57 %

13.11 %

p-NS

Malignancy

18.18 %

22.95 %

p-NS

MEDICATIONS

Any Relevant

42.42 %

68.85 %*

*p<0.05

Steroids >5 mg

28.37 %

32.86 %

p-NS

SOCIAL FACTORS

Smoking

15.15 %

36.06 %*

*p=0.01

Alcohol Use

0

1.63 %

—

In this cohort of patients undergoing DEXA scan, osteoporosis was seen more commonly in 53/175 AA males (30.28%) versus 90/410 white males (21.95%). These AA males were younger than whites (Mean age 56.04) as compared to whites (Mean age 62.64). There were a number of factors present with low BMD. Amongst these, low BMI seemed to be the major contributor to low bone mass in these males. Surprisingly, the patients with low BMD had no difference in the age as compared to those with normal BMD. BMI was similar in both AA and white patients. Other factors such as overall medication use, smoking and respiratory disorders were found to be significantly more prevalent than others but no racial difference was found in the prevalence of the secondary disorders.

Conclusion: The results suggest that racial differences exist in the epidemiology of male osteoporosis and these need to be assessed further. In this cohort osteoporosis was seen in a higher % of AA males as compared to white males and at a younger age but no racial differences were found in the prevalence of known risk factors. Also found  was that Low BMI, smoking and overall medication use may be better associated with low BMD and potentially better predictors than older age and secondary medical disorders. Limitations of this study include its retrospective design and small sample size. Nonetheless these results highlight that the racial differences in prevalence and effect of underlying factors needs to be better quantified in population studies, so that males at risk of OP may be better identified and screened earlier. This may have significant implications on decision to consider screening for OP in males.  


Disclosure:

K. Aujla,
None;

V. Majithia,
None.

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