Association between bone-specific physical activity scores and pQCT-derived measures of bone strength and geometry in healthy young and middle-aged premenopausal women

Bone-strengthening activities (e.g., jumping, running, and gymnastics) have been shown to positively affect bone accrual in growing children [1, 2] and overall bone health in later life [3]. Bone-loading forces from moderate to high intensity in parallel with increasing percent of maximal heart rate or 1 repetition maximum (RM) are recommended to help preserve bone health during adulthood [3]. Numerous studies have utilized various assessment tools (e.g., questionnaires, pedometers, accelerometers) to predict bone strength in both clinical and healthy populations [4‐7], but recently the most common methods for assessing one’s historical bone-loading exercises that affect bone strength have been criticized in different bone quality components as well as different age groups.

Among physical activity questionnaires, the bone-specific physical activity questionnaire (BPAQ) is becoming more widely used to estimate bone-specific loading exercise history and its relation to areal bone mineral density (aBMD) as measured by dual-energy X-ray absorptiometry (DXA). The BPAQ algorithms were developed based on lifetime recreational sports and physical activities that involve ground reaction force (GRF)-derived loading values [4]. Previous findings have shown its positive associations with the aBMD of femoral neck, total hip, lumbar spine, and whole body in healthy young adults [4, 8, 9] and middle-aged older men [10]. In contrast, its relationships with bone strength and architecture have been controversial in different trials. Weeks and Beck [4] reported that past and current BPAQ scores had significant ability to detect bone strength parameters whereas other traditional measures of physical activity (e.g., Bone Loading History Questionnaire; BLHQ, 3-day Physical Activity Record; 3DPAR, Pedometer) did not. Significant associations between the BPAQ and magnetic resonance imaging (MRI)-derived midtibia cortical bone quality were also detected in adolescent females [9]. Rantalainen et al. [11] found that higher scores of BPAQ had more bone mass and robust bone geometry compared to those with lower BPAQ scores. However, Farr et al. [6] found that the modified past year physical activity questionnaire (PYPAQ) predicted better indices of bone strength compared to BPAQ, 3DPAR, and pedometer use in girls.

The BPAQ algorithms have been shown to be related to aBMD, but its relations to volumetric BMD (vBMD), bone strength, and bone geometry as measured by peripheral quantitative computed tomography (pQCT) have not been well studied in healthy young and middle-aged premenopausal women. Therefore, the purpose of this cross-sectional study was to determine whether the BPAQ scores were predictive indices of bone characteristics (vBMD, bone strength, and bone geometry) in young and middle-aged premenopausal women. We hypothesized that there would be positive associations between total BPAQ scores and measures of vBMD and bone quality obtained by pQCT. Also, we hypothesized that these significant relationships would be consistently found in young and middle-aged premenopausal women.

Table 1 shows physical characteristics, body composition, daily calcium intake, and total BPAQ score for each group. There were no significant differences in weight, BMI, and total BPAQ scores between young and middle-aged premenopausal women (p > 0.05). We found a significant age difference between groups and young women were taller (5.6 cm), had greater BFLBM (3.0 kg), and less fat mass (− 4.0 kg) and lower % fat (− 3.6%) than middle-aged premenopausal women (p < 0.05).

Young women had significantly greater values for 15 of the 21 aBMD and vBMD variables measured including the L1-L4 and both left and right total hip and femoral neck (p < 0.05) as compared to middle-aged premenopausal women. Young women also had greater values for all tibia sites measures (p < 0.05). At the 38% site, only cortical area and SSI were greater in young women as compared to middle-aged premenopausal women; while at the 66% site, young women had greater total vBMD, cortical thickness, cortical area, and SSI (p < 0.05). There were no significant differences in tibia 38% (total vBMD, cortical vBMD, cortical thickness, total bone area) and tibia 66% (cortical vBMD, total bone area) between groups (p > 0.05). The results of structural parameters of HSA showed that young women had higher values in dominant and non-dominant legs’ hip strength index, section modulus, and CSMI (p < 0.05) as compared to middle-aged premenopausal women. There was a significant difference in buckling ratio, showing that young women had lower values in both dominant and non-dominant leg (p = 0.001). The post hoc power results for primary outcomes (vBMD, bone strength, and geometry) ranged from 0.47 to 0.99 (Table 2).

There were positive correlations between total BPAQ scores and aBMD of right femoral neck (r = 0.313, p = 0.015) and left femoral neck (r = 0.307, p = 0.017) in young women while no significant relationships were found in middle-aged premenopausal women (p > 0.05). A positive relationship was only observed between tBPAQ score and tibia 38% vBMD in middle-aged premenopausal women (r = 0.283, p = 0.038). None of the vBMD variables were correlated with total BPAQ scores in young women. All bone size variables were associated with total BPAQ score (r = 0.280–0.422, p = 0.03–0.001) in young women while there was only one positive relationship between tibia 38% cortical thickness and total BPAQ score in middle-aged premenopausal women (r = 0.273, p = 0.046) (Table 3). There were no significant associations between total BPAQ scores and structural parameters of HSA in middle-aged premenopausal women (p > 0.05). However, young women had negative associations between total BPAQ and CSMI in both legs and buckling ratio and section modulus in non-dominant leg (p < 0.05) (Table 4). The SSI of tibia 38% (r = 0.350, p = 0.006) and 66% (r = 0.406, p = 0.001) was associated with total BPAQ scores in young women while no relationships were found in middle-aged premenopausal women (Fig. 1).

In both young and premenopausal women, when age, BFLBM, and total BPAQ score were included in a stepwise multiple linear regression analysis, BFLBM was a significant predictor of all aBMD variables, accounting for 7–25.7% (p = 0.043–0.001). In middle-aged premenopausal women, only total BPAQ score predicted 8% of the variance in tibia 38% total BMD (p = 0.038) and 38.7% of the variance in tibia 38% cortical thickness (p = 0.001). The rest of vBMD and geometry variables was explained by the BFLBM (14.5–37.8%, p = 0.004–0.001). In young women, only BFLMB predicted 7.2–53.0% of the variance in vBMD and geometry variables (p = 0.038–0.001) (Table 5).

The aim of this cross-sectional study was to determine if total BPAQ scores were positively related to pQCT-derived measures of bone strength and geometry in healthy young and middle-aged premenopausal women and if these relationships were consistently found in two different age groups. The total BPAQ scores were not significant predictors of vBMD both in young and middle-aged premenopausal women; however, significant relationships were found in bone geometry and bone strength in young women. Also, positive associations between total BPAQ scores and measures of aBMD of dual femoral neck were only found in young women.

BPAQ scores have been shown to have positive associations with aBMD of femoral neck as measured by DXA in adolescent and college-aged females [8, 9] and in young and older men [4, 10]. In the current study, we found consistent positive correlations between total BPAQ scores and aBMD of dual femoral neck in young women (18.0–30.2 years); however, these results were not significant in middle-aged premenopausal women (35.6–50.9 years). Previous studies have indicated that women in their 20s had more positive associations between physical activity and aBMD at the hip and spine [15] as compared to women in their 30s or 40s [16, 17]. It is possible that bone-specific loading exercise would be a significant factor to increase bone mass before the peak bone mass formation which normally occurs around the third decade of life. Ho et al. [18] found that leisure time physical activity was not related to bone mass in women aged 31–40, whereas lean body mass and fat mass were highly related to aBMD. Our study results also demonstrated that BFLBM was a significant predictor of all aBMD sites, accounting for 7–25.7% in middle-aged premenopausal women as well as young women. Other relevant factors such as age, diet, body composition, and health status may be more sensitive to predict bone mass than bone-loading physical activity history estimated by BPAQ scores in middle-aged premenopausal women. We did not detect any relationships between total BPAQ and aBMD of lumbar spine in both age groups. Our findings also supported the previous research that suggests BPAQ scores are not positively related to aBMD of lumbar spine in young women [4, 8]. It seems that the BPAQ algorithm may be more related to aBMD of femoral sites. Our study also analyzed cross-sectional geometrical strength of hip using DXA-based HSA and found negative relationships of total BPAQ scores and HSA parameters (buckling ratio, section modulus, and CSMI) in young women. The magnitude of these associations is relatively weak (r = − 0.25 to approximately − 0.32). Weeks et al. [4] did not find any relationships between BPAQ scores and femoral neck CSMI in young men and women; however, current BPAQ scores predicted variance in lumbar spine index of bone structural strength (38%, p = 0.005). Our study did not measure bone strength in lumbar spine using DXA.

The BPAQ algorithms were developed from ground reaction forces-derived loading values, which account for lifetime physical activity affecting bone health. A two-dimensional imaging tool, DXA, was used to measure bone outcomes (aBMD) and a small number of participants were only young adults (N = 40, mean age = 24.6 years) [4]. It is plausible that BPAQ scores may have limited interpretations across various age groups as well as bone quality parameters (bone strength and bone geometry). Unlike DXA, pQCT uses three-dimensional imaging technology to provide many aspects of bone structure that contribute to bone strength [19]. Bone strength is highly influenced by bone geometry parameters as well as bone-loading physical activity [20, 21]. Much like our aBMD results, total BPAQ scores were significantly related to vBMD measures of tibia bone strength and geometry in young women, but not in middle-aged premenopausal women. Rantalainen et al. [11] also found children and young adults who had higher scores of BPAQ had greater vBMD and robust bone geometry compared to those with lower BPAQ scores. In contrast, BPAQ scores were not significantly associated with bone strength at tibia sites in young girls, as compared to the modified PYPAQ [6]. There are a limited number of studies that focused on the relationships between the BPAQ algorithms and bone quality parameters measured by pQCT in different age groups. Based on our findings, BPAQ scores may be more significant indices to predict aBMD and bone strength in healthy young women, but not in middle-aged premenopausal women.

There are several limitations to our study. It is possible that participants’ recall errors (e.g., lifetime recall) would affect the individual pBPAQ scores, and this error might be more evident in the older premenopausal women as compared to the young women. Our cross-sectional study design does not determine cause and effect relationships. The menstrual cycle status of our participants was determined by self-report and not verified by serum hormone measurements; thus, some participants could have been perimenopause. We did not collect blood and tissue samples, which limits the ability to explore underlying mechanisms.

The total BPAQ score-derived physical activity was a stronger predictor of bone strength and geometry as well as aBMD of femoral sites in young women as compared to middle-aged premenopausal women. Differences in age and site-specific aBMD may also contribute to the interpretation of the BPAQ algorithm. Future intervention studies are needed to further clarify these differences and their implications comparing and contrasting results obtained from objective physical activity assessment tools.