Sex-specific and age-specific characteristics of body composition and its effect on bone mineral density in adults in southern China: a cross-sectional study

Xiao, Zeyu; Tan, Zhiqiang; Shang, Jing; Cheng, Yong; Tang, Yongjin; Guo, Bin; Gong, Jian; Xu, Hao

doi:10.1136/bmjopen-2019-032268

Cited by 12 publications

(6 citation statements)

References 34 publications

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“…While increases in bone mass were observed with rising total FM in this analysis, BMD values for most analyzed regions were negatively correlated with central fat accumulation, as measured based on AOI, in non-obese postmenopausal elderly women. These findings are consistent with those from other studies suggesting that DXA-based AOI values are negatively correlated with bone health ( 16 – 18 ). This result may be attributable to a few underlying mechanisms.…”

Section: Discussionsupporting

confidence: 93%

“…After menopause, woman commonly exhibit changes in body composition consisting of a reduction in gynoid fat together with an increase in central fat in the android region ( 14 , 15 ). The android-to-gynoid fat ratio (AOI) has thus been reported to be a valuable indicator of central (visceral) fat accumulation that is correlated with BMD, but studies have yielded inconsistent findings regarding such a relationship ( 16 – 20 ). Shao et al., for example, found central fat accumulation to be negatively correlated with BMD ( 18 ), whereas Kapus et al.…”

Section: Introductionmentioning

confidence: 99%

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Associations of Fat Mass and Fat Distribution With Bone Mineral Density in Non-Obese Postmenopausal Chinese Women Over 60 Years Old

et al. 2022

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BackgroundBone mineral density (BMD) loss is a major complication of menopause, and this loss is closely associated with Fat mass (FM). The relationship between FM, fat distribution (FD), and BMD in postmenopausal women, however, remains incompletely understood. The present study was thus developed to explore these associations between body fat accumulation, FD, and BMD among non-obese postmenopausal women over the age of 60.MethodsThis was a cross-sectional analysis of 357 healthy postmenopausal women between the ages of 60.2 and 86.7 years. Dual-energy X-ray absorptiometry (DXA) was utilized to measure total and regional BMD as well as fat-related parameters including total FM, android and gynoid fat, body fat percentage (BF%), and total lean mass (LM) for all subjects. The android-to-gynoid fat ratio (AOI) was used to assess FD. Pearson’s correlation testing and multiple regression analyses were used to explore relationships among AOI, LM, FM, and BMD.ResultsBoth LM and FM were positively correlated with total and regional BMD in univariate analysis (all P < 0.01), whereas BMD was not significantly associated with AOI in any analyzed site other than the head. Multivariate linear regression models corrected for age, height, and years post-menopause, revealed a sustained independent positive relationship between FM and BMD (standard β range: 0.141 – 0.343, P < 0.01). The relationship between FM and BMD was unaffected by adjustment for LM (standard β range: 0.132 – 0.258, P < 0.01), whereas AOI had an adverse impact on BMD at most analyzed skeletal sites (total body, hip, femoral neck, arm, leg, and head) (standard β range: −0.093 to −0.232, P < 0.05). These findings were unaffected by using BF% in place of FM (standard β range: −0.100 to −0.232, P < 0.05).ConclusionsIn this cohort of non-obese postmenopausal women over the age of 60 from China, total FM was positively associated with BMD, while AOI was negatively correlated with BMD. As such, a combination of proper weight gain and the control of central obesity may benefit the overall bone health of women after menopause.

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Section: Discussionsupporting

confidence: 93%

Section: Introductionmentioning

confidence: 99%

Associations of Fat Mass and Fat Distribution With Bone Mineral Density in Non-Obese Postmenopausal Chinese Women Over 60 Years Old

et al. 2022

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“…Age and BMI-adjusted partial correlation indicated that total LM had a significant positive correlation with BMD at different regions, and this agreed with the findings of several other studies ( 29 , 38 ). A study by Xiao et al ( 27 ) among women (20–95 years), reported that total LM had a greater protective effect on BMD in premenopausal women. They concluded that the effect of LM on BMD could be ascribed to the mechanical influence of muscle, which generates a positive effect on osteogenesis.…”

Section: Discussionmentioning

confidence: 98%

“…Several studies have attempted to explain their association with BMD ( 21 – 28 ), although research has provided contradicting findings on the contribution of LM and FM to changes in BMD. Some studies have asserted a positive association between LM and BMD ( 27 , 29 ), while others ( 17 ) found that LM, rather than FM, was the strongest predictor of BMD. In contrast, some studies showed that FM ( 30 ) and android /gynoid fat mass ratio (A/G FMR) were positively associated with BMD ( 22 , 31 ).…”

Section: Introductionmentioning

confidence: 99%

The Relationship Between Bone Mineral Density and Body Composition Among Qatari Women With High Rate of Obesity: Qatar Biobank Data

et al. 2022

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Studies have reported inconsistent results for the relationship between body composition and bone mineral density (BMD) among women, especially those with a high rate of obesity. This study aims to examine the association between BMD and body composition among Qatari women. A cross-sectional study, using data from the Qatar Biobank (QBB), was conducted on 2,000 Qatari women aged 18 and over. Measurements were taken by dual-energy X-ray absorptiometry (DEXA) for body composition [visceral fat and android fat (AF)], gynoid fat (GF), trunk fat, total fat mass (TFM), total lean mass (LM) and bone mineral density (BMD), including the lumber spine, neck, femur and total body. The participants were divided into groups of normal and low BMD, based on their T-score. Non-linear regression analysis using the restricted cubic spline method was performed according to the T-score of the total BMD for the fat mass variables. Women with a low BMD (T-score <-1) had significantly lower body composition indicators. LM was positively correlated with BMD at the spine (r = 0.29, p < 0.001), neck (r = 0.32, p < 0.001), and femur (r = 0.28, p < 0.001), as well as total BMD (r = 0.29, p < 0.001) and T-score (r = 0.31, p < 0.001), while the correlatio between TFM and BMD was negative and weak (r = −0.05, <0.017). Results of the non-linear regression indicated that components of fat distribution (TFM, AF, GF and trunk fat) were positively associated with total body T-score. In the adjusted non-liner regression, only a slight increase in T-score was recorded with an increase in FM. The association between FM and BMD was non-linear, suggesting that FM may not be a strong protector of bones among women with high rate of obesity.

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“…on the other hand, increased age can bring about changes of bone geometry, which is mainly manifested as bone expansion [ 22 ]. Furthermore, aging is associated with gradual changes in body composition, typically characterised by decreases in appendicular lean mass and increases in central fat mass [ 23 , 24 ].…”

Section: Discussionmentioning

confidence: 99%

Different associations between waist circumference and bone mineral density stratified by gender, age, and body mass index

Yin

Yan

Yin

et al. 2022

BMC Musculoskelet Disord

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Introduction Investigations of the relationship between waist circumference (WC) and bone mineral density (BMD) have inconsistent and incomprehensive results. We explored the association between WC and BMD at various sites in a large-scale population-based study. Methods We screened 5337 participants from National Health and Nutrition Examination Survey (NHANES) database. BMD was measured using dual-energy X-ray absorptiometry at various skeletal sites. The associations of WC with BMD were evaluated by weighted multivariable logistic regression models and conducted subgroup analyses for gender, age, and BMI. A weighted generalized additive model and a smooth curve fitting were performed to address non-linearity. Results Adjustments for all confounders, in males, WC was negatively correlated to BMD in different age and BMI groups (all the p < 0.05), except for in the lowest BMI group; in females, overall trends of relationships between WC and BMD were negative. However, statistical differences were insignificant in some cases. Additionally, every 1 cm increase in WC for individuals of all ages with normal BMI (18.5 ≤ BMI < 25) was associated with decrease in BMD at each skeletal site, as was the case for men with BMI ≥ 25 kg/m2. For women, the negative association of WC with BMD was evident at the lumbar spine in the youngest age group (8 ≤ Age ≤ 18) with normal BMI. Conclusions The nonlinear associations between WC and BMD at various skeletal sites are gender-, age- and BMI-specific in the NHANES (2006–2006).

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Sex-specific and age-specific characteristics of body composition and its effect on bone mineral density in adults in southern China: a cross-sectional study

Cited by 12 publications

References 34 publications

Associations of Fat Mass and Fat Distribution With Bone Mineral Density in Non-Obese Postmenopausal Chinese Women Over 60 Years Old

Associations of Fat Mass and Fat Distribution With Bone Mineral Density in Non-Obese Postmenopausal Chinese Women Over 60 Years Old

The Relationship Between Bone Mineral Density and Body Composition Among Qatari Women With High Rate of Obesity: Qatar Biobank Data

Different associations between waist circumference and bone mineral density stratified by gender, age, and body mass index

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