TOOTH COUNTS DO NOT PREDICT BONE-MINERAL DENSITY IN EARLY POSTMENOPAUSAL CAUCASIAN WOMEN

Citation
Sa. Earnshaw et al., TOOTH COUNTS DO NOT PREDICT BONE-MINERAL DENSITY IN EARLY POSTMENOPAUSAL CAUCASIAN WOMEN, International journal of epidemiology, 27(3), 1998, pp. 479-483
Citations number
20
Categorie Soggetti
Public, Environmental & Occupation Heath
ISSN journal
03005771
Volume
27
Issue
3
Year of publication
1998
Pages
479 - 483
Database
ISI
SICI code
0300-5771(1998)27:3<479:TCDNPB>2.0.ZU;2-T
Abstract
Background It has been suggested that poor dental status may be a suit able criterion for bone densitometry referral in early postmenopausal women. We evaluated this hypothesis in a cohort of 1365 Caucasian wome n aged between 45 and 59 years, who were enrolled into an internationa l multi-centre trial. Methods Subjects were recruited at four study ce ntres, using population-based techniques. Bone mineral density (BMD) a t the lumbar spine and proximal femur was measured by dual energy x-ra y absorptiometry (DXA) (Hologic QDR 2000). A full physical examination was performed including a tooth count. Results Baseline tooth counts ranged from 0 to 32 (median 26): 84 (6%) subjects were edentulous. Whe n classified according to the WHO criteria 445 (33%) of the subjects w ere osteoporotic at one or more of the skeletal sites analysed; 694 (5 1%) were osteopenic, and 226 (16%) were normal. Adjusting for confound ing variables, there was no significant correlation between tooth coun t and BMD at any skeletal site. Subjects were divided into tertiles of tooth count, and chi(2) tests used to compare the two 'extreme' group s against the WHO criteria for BMD. At each of the six BMD regions the proportion of subjects with normal, osteopenic BMD was similar for bo th teriles. Conclusions We found no relationship between tooth count a nd BMD in early postmenopausal women. This may be because in younger w omen dental status is a reflection more of dietary habits and past den tal surgery than of age-related bone loss. Tooth counts therefore cann ot Be used to identify indiv iduals at risk of osteoporosis.