Bone density in young women is associated with body weight and muscle strength but not dietary intakes

Abstract

Potential determinants of bone mineral density (BMD) were studied cross-sectionally in 115 healthy, sexually mature Caucasian women aged 18 years. Bone mineral density (Hologic QDR1000W) of the lumbar spine, proximal femur (five sites), and distal tibia and fibula; fasting blood and urine calcium biochemistry; serum sex hormone levels (follicular phase); nutrient intakes; aerobic fitness; trunk muscle strength; and habitual activity levels were measured. The effects of heredity were considered by measuring the BMD of 107 of the subjects' mothers. Simple and stepwise regression analysis were used to identify significant determinants of BMD at each of the regions studied. The analysis indicated that significant bivariate correlations exist between BMD at all sites and body weight (r = 0.23-0.47, p < or = 0.01), lean body weight (r = 0.34-0.46), trunk strength (r = 0.27-0.47), physical activity score (r = 0.20-0.25), and aerobic fitness (r = 0.29-0.45). Dietary calcium intake correlated significantly with BMD at the trochanter site only (r = 0.19), and none of the biochemical or hormonal indices measured correlated consistently with BMD at any site. Significant correlations between the BMD of mothers and daughters ranged from r = 0.43 at lumbar spine to r = 0.34 at the intertrochanteric site. Paired t-tests showed the daughters had significantly (p < 0.03) lower BMD than their mothers at the lumbar spine (98 +/- 12% [mean +/- SD]) and significantly higher (p < 0.002) BMD at the femoral neck, trochanter, and total hip sites (110 +/- 16%, 108 +/- 17%, 103 +/- 14%, respectively). When stepwise regression analysis included weight-corrected strength of the trunk flexor muscles (Corr Flex), weight-corrected aerobic fitness (Corr VO2max), physical activity score, and body weight, body weight was the only significant determinant of BMD at all sites. Corr Flex made significant contributions at all sites except the femoral neck, while Corr VO2max made additional contribution at the femoral neck, trochanter, total hip, and shaft of femur sites. These variables accounted for 13-27% of the variance in BMD. The addition of mother's BMD to these independent variables, in stepwise regression analysis, improved the prediction to 18-31% of the variance.

Bone health in ambulatory individuals with multiple sclerosis: Impact of physical activity, glucocorticoid use, and body composition

“…This finding is consistent with previous literature in which weight was a primary predictor of WB, LS, and PF BMD [36][37][38]. Of soft tissue components, lean mass has been shown to be the strongest predictor of BMD in young women without MS [23,[39][40][41][42][43] and in adults and older women without MS [36,[44][45][46][47], whereas other studies have shown that fat mass is associated with bone health [21,23,48]. Differences between these findings may be the result of age, since this may affect soft tissue predictors of BMD, with lean mass being a stronger predictor in young women without MS and fat mass having a stronger association with BMD in postmenopausal women without MS [21][22][23].…”

Age, Weight and Body Mass Index Effect on Bone Mineral Density in Postmenopausal Women

“…However, the mean weight and BMI values of the two groups of patients did not differ significantly. Other studies have also shown an association between body weight (14,15) and BMI (1,11,22,(30)(31)(32)(33) with BMD. But, Saravi et al (4) reported no significant effect of BMI on BMD.…”

“…This disease is characterized by low bone mass and destruction of bone tissue, leading to increased fracture risk (1,2,6). Several studied have shown that in addition to the risk factors such as aging, lack of physical activity, smoking, premature menopause, family history, poor diet and low intake of calcium and vitamin D (3,5,(7)(8)(9)(10)(11)(12), other factors, including body weight (13)(14)(15) and BMI (1,3,5,9,(11)(12)(13)16) are also important in the risk assessment tools, which contribute to osteoporosis and osteoporotic fracture risk. Measurement of body mass index is an inexpensive and valuable technique to guide public health policy, clinical decisions, and evaluation of nutritional status (17)(18)(19).…”

Muscle mass and bone mineral indices: does the normalized bone mineral content differ with age?

“…Ultrasound-derived prediction equations are capable of taking measurements in the field, and are safe and valid in predicting total and regional SM mass (Sanada et al, 2006). Some investigators have shown that prolonged low-tomoderate intensity exercise is independently associated with higher BMD (Nguyen et al, 1998;Hagberg et al, 2001;Pongchaiyakul et al, 2004), while cardiorespiratory fitness (VO 2 peak) is only slightly correlated with bone mineral indices (Henderson et al, 1995;Ryan and Elahi, 1998;Lynch et al, 2002). In this study, VO 2 peak (normalized to body mass) in young women was significantly correlated with BMD (Po0.05), while VO 2 peak (normalized to whole-body SM mass) was not significantly associated with BMD (Table 5).…”