Association between muscle strength and mass and bone mineral density in the US general population: data from NHANES 1999–2002

Described as a disease of the bones, osteopenia and osteoporosis result in reduced bone mass and degeneration of bone tissue structure, which increases susceptibility to bone fragility and fracture [1]. By 2030, there will be 13.5 million people with osteoporosis in the USA, up from 10.2 million in 2010, and projections estimate that over 47 million Americans will be afflicted with osteopenia in 2020 [2‐5]. Osteoporotic fracture is a serious clinical complication of osteoporosis, which is responsible for more than 1.5 million fractures annually [6]. Approximately two million dollars was spent on osteoporosis-related unintentional fractures in 2005, and the costs continue to rise [7]. Due to the growing morbidity and mortality, and expense of healthcare, osteoporosis has emerged as a significant public health issue.

A number of risk factors contribute to osteopenia and osteoporosis, including hormonal factors, low peak bone mass, smoking, low physical activity, race/ethnicity, and low strength and muscle. In assessing the risk of low bone mass, these factors should all be considered. Among them, muscle strength, muscle mass, and BMD have triggered extensive research due to the interdependence of the skeletal and muscular systems. However, the relationship between them is unclear, and the outcomes associated with this relationship are controversial. Ahedi et al. [8] discovered that hip muscle cross-sectional area and muscle strength were positively correlated with hip BMD. Similarly, Zhou et al. [9] also explored the connection between muscle strength and BMD and confirmed that the decrease in muscle strength was positively correlated with the decrease in BMD. Furthermore, in both men and women, a cross-sectional study demonstrated a link between BMD and muscle mass [10]. However, some researchers reported no relationship between muscular strength and BMD. According to a cross-sectional investigation, the isokinetic strength of hip muscles may not contribute to the BMD of the proximal femur [11]. Similarly, a cross-sectional study of 58 women (aged 62.1 ± 4.8 years) indicated an association between body fat mass and BMD of the proximal femur but not in lean body mass or appendicular lean mass (ALM) [12]. The emergence of such contradictory conclusions may be due to different study designs, different muscle measurement instruments, and problems with sample sizes between studies. Therefore, we used data from the larger data of NHANES and a more established method of muscle measurement.

Muscle strength is a measure of how a muscle can exert maximum strength. Presently, most of the research in the area of muscle strength is on grip strength. It mainly focuses on the hand and forearm measurement of power. Nevertheless, the main anatomical area for muscle function measurement is in the lower body, and these muscles are essential for daily activities. Additionally, lower limb strength loss is the biggest risk factor leading to falls and other injuries and disabilities [13, 14]. Thus, it will be of more clinical significance to explore the correlation between lower limb muscle strength and BMD to intervene, protect, and prevent osteoporosis. We evaluated muscle mass by calculating the Appendicular Skeletal Muscle Mass Index (ASMI) [15], and as appendicular muscle mass is less confounded by noncontractile lean body mass differences, we selected it over total lean body mass for our analysis. Therefore, we aimed to explore the feasibility of using the lower extremity muscle peak force (PF) value as an indicator of muscle strength and ASMI to predict BMD based on cross-sectional data from the 1999–2002 NHANES.

We utilized data from the NHANES 1999–2002 for this cross-sectional study. The results of the current study suggest that muscle mass and strength are significantly and positively associated with BMD both in univariate and multivariate linear regression analyses. The strong association between muscle mass and strength and BMD persisted after controlling for multiple covariates.

Previous studies have indicated that muscle strength is closely related to BMD [28]. Similarly, Elhakeem et al. [29] discovered that hip BMD in postmenopausal women was independently associated with peak lower extremity muscular strength; an analysis of 979 postmenopausal women from Finland (mean age 68.1 years) in a population-based study illustrated that both body composition and muscle strength had a substantial impact on bone density [28]; furthermore, research by Seabra et al. [30] demonstrated that in teenagers, lower limb muscular strength was related to BMD and bone mineral content (BMC) across the board; a connection between older people’s muscle mass, strength, and bone mass was shown to be gender-specific in a prospective community-based study [31]. In contrast, our findings indicated that muscular strength and BMD are positively associated and do not differ based on gender. Two considerations might account for the contrast: first, variations in research design, muscle-measuring tools, or statistical correction factors; second, variations in sample sizes between investigations.

By employing ASMI, we later examined the connection between muscle mass and BMD and observed that there was a strong significant relationship between the two variables. This is consistent with the findings of Segal et al. [32], who revealed that muscle mass was positively associated with hip BMD. According to a cross-sectional investigation, the incidence of spinal compression fractures may be substantially related to lower limb muscle mass and grip strength [33]. In addition, compared with the study of Qin et al. [10], our study selected a wider range of people, no longer limited to those under 59 years old. Moreover, for BMD, this study selected a greater amount of regional BMD data, which should ensure that the conclusions of this paper are more rigorous. Compared with some previous studies with small sample-size studies, we utilized nationally representative NHANES data, which improved the external validity. Thus, this survey will give convincing support for the use of ASMI and muscular strength testing for osteopenia and osteoporosis screening methods in the USA.

There has been a struggle among researchers to understand how bone health and muscle are linked. In Bone’s mechanostat theory, mechanical strain applied to bone determines bone remodeling, and bones adapt to static and dynamic forces generated by muscle contractions [34]. As muscles become stronger, they may exert greater stress on their bones, putting them under load and encouraging bone formation and retention, which contributes to bone mass [35]. Skeletal muscle mass increases with an increase in mechanical load, whereas skeletal muscle mass decreases with a decrease in mechanical load [36]. There is evidence that skeletal muscle-derived mechanical loading plays an important role in bone development and maintenance [37, 38]. Besides being mechanically active, skeletal muscle can also function endocrinely to maintain skeletal homeostasis. It is believed that skeletal muscle is an endocrine organ that releases a set of cytokines and a protein called myokines whenever muscles contract. Muscle myokines function autocrinely by controlling muscle metabolism, while bone, fat, brain, and liver myokines function paracrinely [39]. A mouse model of limb muscle removal affects bone growth and mineralization; however, mice receiving minced skeletal muscle, non-limb SKM, or cardiac muscle were able to form cartilage and bone nodules [40]. Animals with fractures where a skeletal muscle segment is excised heal better (and even increase their bone synthesis) when high molecular weight molecules derived from the muscle are infused into the injured area [41, 42]. The skeletal muscle releases actin directly to regulate the interaction between the muscle and the bones. In addition, the underlying mechanisms of muscle effects on BMD, including mechanical and metabolic aspects, still require further investigation.

A gender-based subgroup analysis was conducted to determine if gender affected bone metabolism. In both genders, PF, ASMI, and BMD correlated significantly and positively. The association remained significant after adjusting for multiple confounding factors, suggesting that the relationship was independent of gender.

However, analyses stratified by race/ethnicity in our group showed that ASMI and PF were consistently positively associated with BMD in non-Hispanic whites, whereas associations became less significant in other racial/ethnic groups. And this means that race/ethnicity can influence the association of ASMI and PF with BMD in this study. A cross-sectional study of 1190 community-dwelling men showed that greater bone strength among black American men than among their white counterparts and may indicate elevated fracture risk among older Hispanic American subpopulations [43]. The same is true for women; studies from NHANES III reported higher femoral neck BMD and shorter hip axis length in Mexican American women compared to non-Hispanic white women in the USA [44]. Consistent with the previous study, non-Hispanic whites have been reported to have significantly lower BMD and higher fracture rates compared with non-Hispanic blacks [45‐47]. Moreover, Noel et al. [48] demonstrated differences in BMD and osteoporosis among major racial and ethnic groups, highlighting the need to study individual groups by origin or background. It is worth noting that research by Berenson et al. [49] discovered differences in genetic risk factors, obesity status, alcohol consumption, and other factors across racial/ethnic groups, which may provide a possible explanation for noted race-specific differences. Future studies with larger populations would benefit from examining associations across a wider range of race/ethnicity.

Our research has several advantages. First, it is accomplished by analysis of the NHANES data, a dependable data source for epidemiological studies. There is less likelihood of sampling bias because NHANES contains a substantial representative sample of the whole US population. Moreover, questionnaires and laboratory data sets offer comprehensive demographic, lifestyle, dietary, and medical information. We can better manage possible confounders in multiple regression models with the use of this data. We also have more ability to produce meaningful results thanks to the large sample size that NHANES provides. Finally, the knee extensor peak strength test is a commonly used muscle strength measure. ASMI is easier to obtain with DXA, so both are easier to use as screening tests for low BMD.

The study has several limitations. On the one hand, as a result of the cross-sectional design of this study, causal relationships between muscle strength, mass, and BMD cannot be inferred. On the other hand, even though we included a number of covariables when performing the multivariate regression analysis, there may still be some residual confounding.

We found that muscle mass and strength were significantly and positively associated with BMD in the total, pelvis, and lumbar spine in nationally representative sample of US adults, suggesting that PF and ASMI in the lower extremities may be a screening indicator for low BMD. This makes it easier to intervene early in osteoporosis risk individuals. For future research direction, it is suggested to further explore the causal relationship between muscle mass, strength, and BMD. This will be very helpful for our future research.