Abstract
Objective
Previous studies have shown that grip strength reflects not only muscle function but also relates to bone mineral density (BMD) in adults. However, its association with BMD in adolescents remains unclear. This study aimed to examine the correlation between grip strength and BMD among US adolescents aged 12–19 years.
Methods
Data were drawn from the National Health and Nutrition Examination Survey (NHANES) 2011–2014, including 1,752 adolescents aged 12–19 years. Combined grip strength was defined as the sum of the maximum readings from each hand using a hand-held dynamometer. BMD of the right leg, trunk, and whole body was measured using dual-energy X-ray absorptiometry (DXA). Univariate and multivariate linear regression models were applied to assess the relationship between grip strength and BMD.
Results
After adjustment for age, ethnicity, body mass index (BMI), smoking status, alcohol consumption, calcium and vitamin D supplementation, and serum calcium and phosphorus levels, grip strength showed a positive association with right leg BMD [β = 0.004, 95% CI: (0.004, 0.004)], trunk BMD [β = 0.004, 95% CI: (0.004, 0.004)], and whole-body BMD [β = 0.003, 95% CI: (0.003, 0.004)] (p < 0.001).
Conclusions
(1) Grip strength was positively associated with right leg, trunk, and whole-body BMD among American adolescents aged 12–19 years. (2) Hand grip strength may serve as a useful indicator in assessing skeletal health in this age group.
| What is Known: |
| • A significant positive association persists between handgrip strength and bone mineral density among adolescents. |
| What is New: |
| • Literature is not avallable regarding sports participation and pubertal status with bone mineral density in adolescents. |
Keywords: Handgrip strength, Bone mineral density, Adolescents, NHANES
Introduction
Osteoporosis is a systemic skeletal disease characterized by reduced bone mass and deterioration of bone microarchitecture, which increases bone fragility and fracture risk [1]. As the global population continues to age, the economic impact of osteoporotic fractures is becoming more severe, with estimated costs reaching around $1.7 billion annually in the United States and £900 million in the United Kingdom [2, 3]. The primary contributor to osteoporotic fractures is decreased bone mass, which may result from age-related loss or failure to reach optimal peak bone mass during growth. Notably, bone mass accrued during early life is considered the most significant modifiable factor affecting skeletal health across the lifespan [4]. For this reason, monitoring bone mineral density (BMD) during adolescence is vital for osteoporosis prevention.
Muscles and bones function as interconnected components of the human motor system. A meta-analysis encompassing 39 studies has demonstrated a relationship between muscle strength and bone health from childhood to early adulthood, suggesting that muscle strength can serve as a valuable marker of bone condition during growth and development [5]. Adolescents with lower athletic ability have also been shown to exhibit poorer bone health [6]. With age, muscle mass and bone mass often decline concurrently [7]. Findings from several cross-sectional studies support this observation [8–10]. Thus, muscle strength may serve as an indicator in evaluating skeletal health in adolescents.
Skeletal muscle strength refers to the amount of force muscles can produce [11]. Research indicates that grip strength is linked to the strength of nearly all major muscle groups in the body [12]. Based on this, we propose that grip strength may act as a practical measure of skeletal muscle strength. This study investigates whether grip strength can be used to predict BMD in adolescents and aims to offer guidance for preventing osteoporosis later in life.
Methods
Data source
The National Health and Nutrition Examination Survey (NHANES) is a program designed to evaluate the health and nutritional status of adults and children in the United States. It collects demographic information, health-related questionnaires, clinical examination data, and physiological measurements. All procedures are carried out by trained medical personnel, and the resulting data help assess nutritional status, disease prevalence, and related risk factors. These data provide essential public health statistics for national use [Centers for Disease Control and Prevention (CDC), http://cdc.gov/nchs/nhanes]. This study used data from the 2011–2012 and 2013–2014 survey cycles. Written informed consent was obtained from all participants before any data collection.
Measurement of grip strength index
Participants were instructed to squeeze a dynamometer with maximum effort while exhaling to prevent elevated intrathoracic pressure. The procedure was then repeated using the opposite hand. Each hand was tested three times, alternating between hands, with a 60-s rest between trials for the same hand. From these six trials, the highest value from each hand was selected and summed to calculate the combined grip strength. Data for this measurement were taken from the MGX-G and MGX-H datasets.
Measurement of bone mineral density
Dual-energy X-ray absorptiometry (DXA) is widely recognized for its efficiency, convenience, and low radiation exposure when assessing body composition [13]. Whole-body scans were conducted using a Hologic Discovery model A densitometer (Hologic, Inc., Bedford, Massachusetts) with Apex software version 3.2. Certified and trained radiologic technicians conducted all DXA exams, maintaining strict quality control during both data collection and scan analysis. Given the close relationship between grip strength and upper-arm musculature, we excluded upper-arm BMD and focused on BMD in the right leg, trunk, and the whole body. Data for BMD were sourced from the DXX-G and DXX-H sections.
Other covariates
Based on prior studies examining the relationship between grip strength and bone mineral density [12, 16, 17], we identified several covariates and potential confounding factors. These included age, gender, ethnicity (Mexican American, non-Hispanic Black, non-Hispanic White, other Hispanic, and other racial groups), and the family income-to-poverty ratio. The ratio was categorized as low (< 1.3), moderate (1.3–3.5), and high (> 3.5) [14]. These demographic variables were sourced from DEMO_G and DEMO_H. Body mass index (BMI) was calculated by dividing weight by height squared (kg/m2). Considering the specific characteristics of the adolescent population, we also included BMI z-scores, a variable created for individuals aged 2 to 19 years. These scores are based on the CDC’s 2000 sex-specific BMI-for-age growth charts for the United States. The age in months at the time of examination was matched with corresponding values from the growth chart, separately for males and females. BMI z-scores were categorized as follows: (1) Underweight (BMI < 5th percentile), (2) Normal weight (BMI 5th to < 85th percentile), (3) Overweight (BMI 85th to < 95th percentile), and (4) Obese (BMI ≥ 95th percentile). These data were obtained from BMX_G and BMX_H. Smoking status was determined by responses to the question “Do you smoke now?” Participants who answered"Every day"or"Some days"were classified as having a smoking habit, while those who answered “Not at all” were considered non-smokers. These data came from SMQ_G and SMQ_H. Alcohol consumption was classified based on whether a participant reported drinking alcohol at least 12 times in the past year. Those who met this criterion were identified as having a drinking habit. These data were from ALQ_G and ALQ_H. Use of vitamin D and calcium supplements was assessed based on whether the participant had taken either supplement in the previous 30 days. This information was obtained from DSQTOT_G and DSQTOT_H. Serum calcium levels were measured using the DxC800 system, which applies an indirect (diluted) ion-selective electrode (I.S.E.) method. Serum phosphorus concentration was measured using a timed-rate method, also via the DxC800 system. Data for both indicators were sourced from BIOPRO_G and BIOPRO_H. These variables were adjusted for in the multiple linear regression analysis and, when appropriate, applied as stratification factors in subgroup analyses.
Statistical analysis
In all analyses, continuous variables are presented as mean ± standard error (SE), while categorical variables are shown as counts and percentages. All continuous variables included in the regression models were tested for normality using the Anderson–Darling and Kolmogorov–Smirnov tests. Gender differences were assessed using Student’s two-tailed t-test or the Rao–Scott chi-square test.
Combined grip strength values were divided into quartiles, with Q1 representing the lowest values and Q4 the highest. Multivariable-adjusted logistic regression models were applied to examine the associations between combined grip strength quartiles and BMD of the right leg, trunk, and whole body. Three models were constructed to assess the independent relationship between BMD and grip strength: Model 1 included no adjustments; Model 2 adjusted for age, gender, and ethnicity; Model 3 further adjusted for age, gender, ethnicity, income-to-poverty ratio, BMI, smoking status, alcohol consumption, use of vitamin D and calcium supplements, serum calcium, and serum phosphorus levels.
Sampling weights were applied based on the weighting guidelines provided by NHANES. Four-year weights for the 2011–2012 and 2013–2014 cycles were calculated by multiplying the respective two-year weights by 0.5. All statistical analyses were performed using EmpowerStats (www.empowerstats.com) and R (http://www.R-project.org). A p-value < 0.05 was considered statistically significant.
Results
A total of 1,752 participants were included in the study, comprising 922 boys (mean age 15.4 ± 2.3 years) and 830 girls (mean age 15.2 ± 2.2 years). The distribution of ethnicities was relatively balanced between the two groups. No significant differences were found between boys and girls in smoking status, alcohol consumption, use of vitamin D or calcium supplements, or BMI. However, boys showed significantly higher values than girls in income-to-poverty ratio, serum calcium, serum phosphorus, combined grip strength, and BMD of the right leg, trunk, and whole body (p < 0.05) (Fig. 1, Table 1).
Fig. 1.
Flow chart algorithm
Table 1.
Characteristics of study sample
| Characteristic variable | Total N = 1752 | p-Value | |
|---|---|---|---|
| Boy N = 922 | Girl N = 830 | ||
| Age (year) | 15.4 ± 2.3 | 15.2 ± 2.2 | < 0.05 |
| Ethnicity (%) | 0.95 | ||
| MexicanAmerican | 14.8 | 14.5 | |
| Other Hispanic | 6.5 | 7.4 | |
| Non-Hispanic White | 56.4 | 56.2 | |
| Non-Hispanic Black | 13.9 | 13.6 | |
| Other multiracia | 8.4 | 8.3 | |
| Smoking habit (%) | 0.33 | ||
| YES | 2.3 | 1.7 | |
| NO | 97.7 | 98.3 | |
| Drinking habit (%) | 0.35 | ||
| YES | 22.0 | 24.0 | |
| NO | 78.0 | 76.0 | |
| Use of calcium supplements (%) | 0.87 | ||
| YES | 13.8 | 133 | |
| NO | 86.2 | 86.7 | |
| Use of Vitamin-D supplements (%) | 0.78 | ||
| YES | 17.4 | 18.0 | |
| NO | 82.6 | 82.0 | |
| BMI z-scores(%) | < 0.05 | ||
| 1 | 4.9 | 1.8 | |
| 2 | 58.3 | 59.8 | |
| 3 | 17.4 | 16.3 | |
| 4 | 19.5 | 22.1 | |
| Income poverty ratio | 2.49 ± 1.63 | 2.34 ± 1.59 | < 0.05 |
| BMI(kg/m2) | 23.82 ± 5.80 | 24.44 ± 6.67 | < 0.05 |
| Serum calcium level (mg/dL) | 9.68 ± 0.29 | 9.59 ± 0.30 | < 0.05 |
| Serum phosphorus level (mg/dL) | 4.47 ± 0.74 | 4.25 ± 0.59 | < 0.05 |
| Combined grip strength (kg) | 74.16 ± 20.35 | 54.02 ± 9.93 | < 0.05 |
| Right leg BMD (g/cm2) | 1.141 ± 0.154 | 1.074 ± 0.109 | < 0.05 |
| Total BMD (g/cm2) | 1.045 ± 0.131 | 1.017 ± 0.099 | < 0.05 |
| Trunk Bone BMD(g/cm2) | 0.871 ± 0.138 | 0.853 ± 0.100 | < 0.05 |
Values are expressed as mean ± SD or percentages; BMI, body mass index; BMD, bone mineral density.
Table 2 presents the distribution of participants across quartiles of combined grip strength. Age, sex, ethnicity, alcohol consumption, smoking status, BMI, income-to-poverty ratio, calcium supplement use, serum calcium, and serum phosphorus were all significantly associated with grip strength quartiles. Regarding the outcome variables, BMD of the right leg, trunk, and whole body all increased progressively with higher grip strength quartiles, and these associations were statistically significant.
Table 2.
Distribution of combined grip strength (22.4–130 kg) and other covariates in relation to BMD
| Variables | Q1 (22.4–49.3) N = 430 |
Q2(49.3–60.06) N = 439 |
Q3(60.06–70.82) N = 436 |
Q4(70.82–130) N = 447 |
P-value |
|---|---|---|---|---|---|
| Age (year) | 13.7 ± 1.9 | 15.0 ± 2.1 | 15.51 ± 2.0 | 16.9 ± 1.7 | < 0.05 |
| Gender(%) | < 0.05 | ||||
| Boy | 33.3 | 22.8 | 57.8 | 96.4 | |
| Girl | 66.7 | 77.2 | 42.2 | 3.6 | |
| Ethnicity(%) | < 0.05 | ||||
| Mexican American | 18.0 | 13.5 | 15.0 | 12.5 | |
| Other Hispanic | 9.2 | 7.2 | 4.5 | 6.6 | |
| Non-Hispanic White | 56.2 | 59.0 | 52.6 | 57.3 | |
| Non-Hispanic Black | 8.4 | 12.9 | 18.1 | 15.6 | |
| Other ethnicities | 8.2 | 7.4 | 9.8 | 8.0 | |
| Smoking habit (%) | < 0.05 | ||||
| YES | 0.6 | 1.5 | 1.2 | 5.1 | |
| NO | 99.4 | 98.5 | 98.8 | 94.9 | |
| Drinking habit (%) | < 0.05 | ||||
| YES | 7.4 | 18.4 | 20.6 | 43.7 | |
| NO | 92.6 | 81.6 | 79.4 | 56.3 | |
| Use of calcium supplements (%) | < 0.05 | ||||
| YES | 20.0 | 14.6 | 19.7 | 18.2 | |
| NO | 80.0 | 85.4 | 80.3 | 81.2 | |
| Use of Vitamin-D supplements (%) | < 0.05 | ||||
| YES | 20.0 | 19.5 | 23.8 | 16.3 | |
| NO | 80.0 | 80.5 | 76.2 | 83.7 | |
| BMI z-scores(%) | < 0.05 | ||||
| 1 | 6.5 | 1.4 | 2.4 | 3.4 | |
| 2 | 70.3 | 57.8 | 56.6 | 51.9 | |
| 3 | 9.8 | 20.2 | 15.6 | 21.4 | |
| 4 | 13.4 | 20.6 | 25.3 | 23.3 | |
| Income poverty ratio | 2.54 ± 1.62 | 2.42 ± 1.62 | 2.50 ± 1.61 | 2.24 ± 1.59 | < 0.05 |
| BMI (kg/m2) | 21.25 ± 5.48 | 24.25 ± 6.22 | 24.80 ± 6.16 | 25.94 ± 6.03 | < 0.05 |
| Serum calcium level (mg/dL) | 9.66 ± 0.31 | 9.60 ± 0.30 | 9.64 ± 0.30 | 9.66 ± 0.29 | < 0.05 |
| Serum phosphorus level (mg/dL) | 4.63 ± 0.65 | 4.38 ± 0.73 | 4.35 ± 0.68 | 4.14 ± 0.58 | < 0.05 |
| Right leg BMD (g/cm2) | 0.982 ± 0.102 | 1.073 ± 0.090 | 1.139 ± 0.105 | 1.234 ± 0.115 | < 0.05 |
| Total BMD (g/cm2) | 0.928 ± 0.094 | 1.009 ± 0.085 | 1.053 ± 0.094 | 1.130 ± 0.096 | < 0.05 |
| Trunk Bone BMD(g/cm2) | 0.753 ± 0.096 | 0.843 ± 0.086 | 0.887 ± 0.098 | 0.958 ± 0.105 | < 0.05 |
Values are expressed as mean ± SD or percentages; BMI, body mass index; BMD, bone mineral density.
Table 3 displays the multivariable regression analysis results for combined grip strength and BMD of the right leg, trunk, and whole body. In the fully adjusted model, combined grip strength was positively associated with BMD at all three sites (all p < 0.05). These associations remained significant in trend analyses based on grip strength quartiles (all trend p < 0.05). Smooth curve fitting indicated a linear relationship between combined grip strength and BMD of the trunk and whole body (Fig. 2).
Table 3.
Association between combined grip strength (22.4–130 kg) and right leg, trunk, and whole-body BMD
| Model1 β(95% CI) |
Model2 β(95% CI) |
Model3 β(95% CI) |
|
|---|---|---|---|
| Right leg BMD | 0.005 (0.005, 0.005) | 0.005 (0.004, 0.005) | 0.004 (0.004, 0.004) |
| Q1(22.4–49.3) | Reference | Reference | Reference |
| Q2(49.3–60.06) | 0.091 (0.078, 0.105) | 0.069 (0.055, 0.082) | 0.056 (0.043, 0.069) |
| Q3(60.06–70.82) | 0.157 (0.143, 0.171) | 0.157 (0.143, 0.171) | 0.157 (0.143, 0.171) |
| Q4(70.82–130) | 0.252 (0.238, 0.266) | 0.252 (0.238, 0.266) | 0.252 (0.238, 0.266) |
| P for trend | < 0.05 | < 0.05 | < 0.05 |
| Trunk bone BMD | 0.004 (0.004, 0.004) | 0.004 (0.004, 0.005) | 0.004 (0.004, 0.004) |
| Q1(22.4–49.3) | Reference | Reference | Reference |
| Q2(49.3–60.06) | 0.090 (0.078, 0.103) | 0.090 (0.078, 0.103) | 0.090 (0.078, 0.103) |
| Q3(60.06–70.82) | 0.134 (0.121, 0.147) | 0.134 (0.121, 0.147) | 0.134 (0.121, 0.147) |
| Q4(70.82–130) | 0.205 (0.192, 0.217) | 0.205 (0.192, 0.217) | 0.205 (0.192, 0.217) |
| P for trend | < 0.05 | < 0.05 | < 0.05 |
| Whole body BMD | 0.004 (0.004, 0.004) | 0.004 (0.003, 0.004) | 0.003 (0.003, 0.004) |
| Q1(22.4–49.3) | Reference | Reference | Reference |
| Q2(49.3–60.06) | 0.081 (0.068, 0.093) | 0.081 (0.068, 0.093) | 0.081 (0.068, 0.093) |
| Q3(60.06–70.82) | 0.124 (0.112, 0.137) | 0.124 (0.112, 0.137) | 0.124 (0.112, 0.137) |
| Q4(70.82–130) | 0.201 (0.189, 0.213) | 0.201 (0.189, 0.213) | 0.201 (0.189, 0.213) |
| P for trend | < 0.05 | < 0.05 | < 0.05 |
Model 1: unadjusted.
Model 2: adjusted for age, sex, and ethnicity.
Model 3: Adjusted for age, sex, ethnicity, smoking and drinking habits, use of calcium and vitamin D supplements, income-to-poverty ratio, BMI z-scores, serum calcium, and serum phosphorus levels.
p-values were corrected for multiple comparisons using permutation testing.
Fig. 2.
Association between combined grip strength and trunk and whole-body BMD. 1. Each black point represents a sample. 2. The solid red line indicates the fitted smooth curve between variables. The blue bands represent the 95% confidence interval of the fit. The following covariates were adjusted: age, sex, ethnicity, smoking status, alcohol consumption, use of calcium and vitamin D supplements, income-to-poverty ratio, BMI z-scores, serum calcium, and phosphorus levels
Table 4 presents the results of the stratified analysis by gender and BMI z-scores. The association between combined grip strength and BMD was stronger among girls, with all interaction p < 0.05.
Table 4.
Association between combined grip strength and BMDs, stratified by gender BMI z-scores groups
| Subgroup | Trunk bone BMD β (95% CI) |
Right leg BMD β (95% CI) |
whole body BMD β (95% CI) |
|---|---|---|---|
| Gender | |||
| Boy | 0.004 (0.003, 0.004) | 0.004 (0.003, 0.004) | 0.003 (0.003, 0.003) |
| Girl | 0.004 (0.004, 0.005) | 0.004 (0.004, 0.005) | 0.004 (0.003, 0.004) |
| P for interaction | 0.035 | 0.004 | 0.018 |
| BMI z-scores | |||
| 1 | 0.005 (0.004, 0.006) | 0.006 (0.005, 0.007) | 0.005 (0.003, 0.006) |
| 2 | 0.004 (0.004, 0.004) | 0.004 (0.004, 0.005) | 0.003 (0.003, 0.004) |
| 3 | 0.004 (0.003, 0.004) | 0.004 (0.003, 0.004) | 0.003 (0.003, 0.004) |
| 4 | 0.004 (0.003, 0.004) | 0.004 (0.003, 0.004) | 0.003 (0.003, 0.004) |
| P for interaction | 0.066 | 0.001 | 0.119 |
Adjusted for age, sex, ethnicity, smoking status, drinking status, use of calcium and vitamin D supplements, income-to-poverty ratio, BMI z-scores, serum calcium, and phosphorus levels, excluding the stratification variables themselves.
Discussion
This study examined the relationship between combined grip strength and BMD of the right leg, trunk, and whole body in American adolescents aged 12–19 years. Using a nationally representative dataset and adjusting for all relevant covariates, the weighted multiple linear regression analysis showed a significant positive correlation between grip strength and BMD at all three skeletal sites.
The link between grip strength and BMD, as well as its relevance to osteoporosis and fracture risk, has been widely reported in various populations, including the general adult population, older adults, and postmenopausal women. For instance, a Mendelian randomization study reported a positive causal relationship between grip strength and lumbar spine BMD [15]. Another cross-sectional study suggested that hand grip strength reflects BMD at remote skeletal sites such as the lumbar spine and hip, and may serve as a practical indicator across different genders and menopausal statuses in the general U.S. population [16]. Although debate continues about whether muscle strength influences BMD locally or more generally across the body, some researchers have suggested that the impact of muscle strength may not be limited to adjacent bone regions [27]. Furthermore, studies involving middle-aged and elderly individuals have shown that greater grip strength is linked to higher BMD, even after controlling for BMI, physical activity, and other confounding variables [17]. However, the evidence supporting such associations in adolescents remains limited. Adolescence is a period marked by rapid bone mass gain, which contributes to peak bone mass, a key factor in determining long-term skeletal health [18]. Peak bone mass is typically reached earlier in the spine and hip than in the rest of the body. This developmental trajectory is influenced by both genetic and environmental factors, including nutrition, socioeconomic status, physical activity, and gender [19, 20]. Research on younger populations supports the connection between muscle strength and bone development. A study of over 300 children aged 10–12 years found a consistent relationship between muscle strength and bone mass, with grip strength emerging as an independent predictor [21]. Similarly, a study involving 560 school-aged children (6–12 years) reported a significant positive association between grip strength and BMD [22].
The regulation of skeletal muscle and bone mass is influenced by multiple factors, including mechanical stimuli [23, 24]. Mechanical forces generated by muscle contractions act on bones, indirectly affecting both bone mass and strength [25–27]. In addition to mechanical loading, muscle fibers release myokines, which influence bone metabolism, growth, and repair through complex signaling pathways [29–36]. These myokines circulate throughout the bloodstream [28], which may partly explain why grip strength correlates with bone mineral density across various skeletal sites. Whether mechanical loading stimulates myokine production, and whether myokine activity changes with age, remains an area for further investigation. Prior to reaching peak bone mass, the combined effects of mechanical loading and endocrine signaling play a greater role in bone formation. Muscle mass and bone mass are strongly correlated, and increases in muscle mass are predictive of gains in bone mass [37].
The association between greater grip strength and higher BMD at the radial bone in the forearm under mechanical load has been documented [38], though this relationship may be both site-specific and systemic. Local increases in bone formation may positively influence bone metabolism at more distant skeletal sites, suggesting a broader systemic effect. Some studies have reported that grip strength is also a predictor of lumbar spine BMD [39], further supporting its potential as a proxy measure of skeletal status in other regions. Grip strength may serve as a useful marker for assessing skeletal development and identifying strategies to help adolescents reach optimal peak bone mass, which can reduce the risk of osteoporosis-related fractures later in life. Previous research has shown that the relationship between physical activity and bone mass can be observed as early as childhood (ages 5–11) [40], and individuals with higher levels of physical activity tend to have greater bone mineral content [41]. Additional findings suggest that weight-bearing activities are more strongly associated with bone mineral status than non-weight-bearing activities [42], likely due to the influence of muscle strength, as physically active individuals typically have better muscle condition [43]. However, it is important to recognize that while lean mass, primarily muscle, contributes more to BMD than fat mass [44], performing grip strength training alone may not directly improve BMD in areas like the hip and lumbar spine.
In addition, our study found that the association between grip strength and BMD in adolescents is influenced by gender, consistent with findings reported by Hyde [45]. Stratified analysis revealed a stronger correlation between combined grip strength and trunk BMD in boys than in girls. This may be partly explained by differences in physical activity patterns, as adolescent boys are more likely to participate in competitive and weight-bearing sports, which can contribute to higher BMD. However, such differences are not typically observed before puberty [46]. Boys generally enter puberty 1–2 years later than girls, resulting in a longer skeletal growth period. Physiological differences in bone development also play a role. Periosteal expansion in boys leads to greater cortical thickness, whereas girls experience more endosteal apposition [47]. Consequently, boys tend to reach peak BMD later than girls. The differing timing and biological mechanisms of bone development between sexes likely contribute to the gender-specific variation in the relationship between grip strength and BMD. We also observed that during adolescence, both grip strength and BMD increase with age. This supports the use of grip strength as a reference for tracking age-related changes in BMD. Peak bone mass is typically achieved around age 20, earlier in girls than boys [48]. However, peak grip strength generally occurs between ages 30 and 40, after which it gradually declines due to various physiological and lifestyle factors [49–52].
Our study also found a positive association between BMI and grip strength, aligning with the findings of Cooper [26]. Prior research has also supported the relationship between BMI, other anthropometric indicators, and BMD [27, 53, 54]. Individuals with higher grip strength usually have greater skeletal muscle mass, and lean body mass, primarily composed of muscle, significantly contributes to BMI. As such, the observed association between BMI and BMD may, in part, be mediated by grip strength [27].
This study has several limitations. First, although NHANES employed a complex multistage probability sampling design, the cross-sectional nature of the dataset prevents us from testing any causal relationship between grip strength and BMD. Second, while multiple covariates were controlled in the multivariable regression analysis, bone mass in adolescents aged 12–19 years is influenced by a wide range of factors. Variables such as sports participation and pubertal status, which are closely tied to musculoskeletal development, were not included in this analysis. Additionally, the exclusion of participants with missing data may have introduced bias. It also remains unclear whether the strength of the association between grip strength and BMD varies across different skeletal sites and between genders. Given the integrated nature of the human motor system, the effect of muscle strength on BMD may not follow a direct one-to-one pattern between specific muscle groups and bone sites. This complexity suggests that the interaction between muscular and skeletal development is not uniformly distributed throughout the body. Expanding the study to include a wider age range may help clarify these relationships.
In conclusion, this cross-sectional study found a positive correlation between hand grip strength and BMD in the right leg, trunk, and whole body among American adolescents aged 12–19 years. This association persisted after adjusting for BMI and sex, suggesting that grip strength may serve as a practical indicator for evaluating bone health during adolescence.
Acknowledgements
All of the investigators and staff members were gratefully acknowledged. Thanks for all the enthusiastic participants
Authors’ contributions
This study was designed by Shun Yang. Zhongqing Wang extracted the associated data from NHANES,Keyi Chen performed the statistical analysis. Zhognqing Wang completed the composition of the manuscript, helped supervised the analysis, and revised and approved the manuscript.
Funding
None.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethical approval
This study strictly adhered to the principles of the Declaration of Helsinki from beginning to end. While protecting the rights and interests of the subjects, we are committed to conducting high-quality research work.The studies involving human participants were reviewed and approved by NHANES. The patients/participants provided their written informed consent to participate in this study.
Conflicts of interest
The authors declare no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
No datasets were generated or analysed during the current study.