Bone mineral density and adipose tissue distribution in young women: relationship to smoking status

Body fat distribution is associated with lumbar spine bone density independently of body weight in postmenopausal women

OBJECTIVE

To assess the association between the body fat distribution and axial bone mineral density (BMD) in postmenopausal women with or without hormone replacement therapy (HRT).

DESIGN

Cross-sectional population-based study.

SETTING

University of Eastern Finland, Bone and Cartilage Research Unit, Kuopio, Finland.

POPULATION

198 postmenopausal women, mean age 67.5 (1.9 SD), mean BMI 27.1 (3.9 SD).

METHODS

Regional body composition and BMD assessed by dual X-ray absorptiometry (DXA, Prodigy).

MAIN OUTCOME MEASURES

Spinal and Femoral BMD.

RESULTS

Out of the body composition parameters, FM was the main determinant of postmenopausal bone mass. Only the lumbar spine (L2-L4) BMD, not the femoral neck BMD, was positively associated with the trunk FM. Positive trends for association were revealed between the spinal BMD and the trunk FM regardless of the use of HRT. Adjustments did not change the results.

CONCLUSIONS

Higher trunk fat mass was associated with the spinal BMD, but not with the hip BMD in postmenopausal women, irrespective of the HRT use. In addition to biological factors, uncertainties related to DXA measurements in patients with varying body mass may contribute to this phenomenon.

Gynecological factors and body mass index as determinants of bone mass in normal postmenopausal women. A study with peripheral quantitative computed tomography (pQCT)

OBJECTIVE

This paper studied the influence of several gynecological factors (years since menopause (YSM), age at menarche and gynecological age or reproductive life) simultaneously with anthropometric factors as determinants of bone mass in 189 healthy postmenopausal women.

METHODS

Bone mass was determined by peripheral quantitative computed tomography.

RESULTS

An overall evaluation showed that YSM correlated negatively with trabecular and cortical bone density (BMDTrab and BMDCorti) (P<0.05 in both cases). Age at menarche correlated negatively with BMDCorti (P<0.05) and gynecological age correlated positively with BMDTrab (P<0.05). Classifying the women according to their body mass index (BMI), the YSM correlation persisted in those subjects whose BMI was >25 kg/m(2), and in age at menarche and gynecological age of women whose BMI was <25 kg/m(2) (P<0.05). After separating women according to their age at menarche, their gynecological age and BMI, the only significant difference that persisted was in BMDTrab which was lower in the group with gynecological age <33 years, with a BMI <25 kg/m(2) (P=0.020). Parity and smoking had no impact on our results. By multiple regression, with BMD as the dependent variable and the gynecological factors as independent variables, we only observed significance between YSM and BMDCorti (P<0.005). The same was observed after separating women according to their BMI in the >25 kg/m(2) group (P<0.05).

CONCLUSIONS

Our data stress the importance of YSM on BMDTrab and BMDCorti, of age at menarche on BMDCorti and of gynecological age on BMDTrab. However, YSM is the gynecological factor that mainly determines BMD. The differences observed between measurements taken with pQCT and other methods commonly used to estimate bone mass indicate that results obtained with one technique cannot be extrapolated to other methods.

Premenopausal smoking and bone density in 2015 perimenopausal women

The importance of cigarette smoking in relation to bone mass remains uncertain, especially in younger women. In a recent meta-analysis including 10 studies in premenopausal women no effect was seen in this age group. We used baseline data from a large national cohort study (Danish Osteoporosis Prevention Study [DOPS]) to study the cumulated effect of pre- and perimenopausal smoking on bone mineral density (BMD) measured shortly after the cessation of cyclic bleedings. Baseline observations on 2015 recently menopausal women were available. Eight hundred thirty-two women were current smokers and 285 were exsmokers. Significant negative associations of cigarette smoking coded as current, ex-, or never smoking were seen on bone mass in the lumbar spine (P = 0.012), femoral neck (P<0.001), and total body (P<0.001). Quantitatively, the differences between current smokers and never smokers were limited to 1.6, 2.9, and 1.9%, respectively. A statistical interaction was found between smoking and fat mass, indicating that women in the highest tertile of fat mass were unaffected by cigarette smoking. Serum vitamin D levels and osteocalcin were inversely related to the number of cigarettes smoked per day (r = 0.11 and P<0.001; r = 0.17 and P = 0.04), respectively. Bone alkaline phosphatase (BALP) and urinary hydroxyproline (U-OHP) were unaffected by current smoking. The average cumulated effect of premenopausal smoking on bone is small but biologically significant. Reduced body mass in smokers explains part of the negative effect on the skeleton and a complex interaction between smoking and fat mass on the skeleton is indicated. Serum levels of 25-hydroxyvitamin D (25-OHD) and osteocalcin are lower in smokers, which may effect rate of bone loss.

Anthropometry fails in classifying bone mineral status in postmenopausal women

This study tested two hypotheses: (1) that simple anthropometric parameters can be used to identify patients at risk of decreased bone mineral content and (2) that an inverse relationship exists between waist:hip ratio (WHR) and bone mineral density (BMD). Bone mineral content (BMC) and BMD were evaluated by dual-energy X-ray absorptiometry in 1873 free-living women. Of these, 1819 (97%) were post-menopausal. One thousand and thirteen women (54%) had normal BMD, 705 (38%) osteopenia and 155 (8%) osteoporosis. Body weight (Wt), body mass index and arm muscle and fat areas were significantly lower in osteoporotics than osteopenics (p < 0.0001) and in these latter than controls (p < 0.0001). However, values of WHR were similar in all groups (p = ns). Body weight was the anthropometric parameter better correlated with BMC (rho = 0.650, p < 0.0001) and only Wt and age were identified as significant predictors of bone mineral status (normal-BMD/osteopenic/osteoporotic) at polytomous logistic regression (p = 0.0001 for each). However, Wt could not be employed as an indicator of bone mineral status at the individual level because of high variations in BMC for the same level of Wt. Under- (< 5th percentile) and normal-Wt (5th-95th percentile) women had the same frequency of osteopenia (39%) while it was lower in over-Wt (> 95th) women (13%). The frequency of osteoporosis was higher in under- than normal-Wt women (37 vs 7%) and none of the over-Wt women had osteoporosis. This study shows that: (1) simple anthropometric measurements cannot be used to select subjects at risk of decreased BMC and, (2) BMD does not vary with WHR.